CN108697889B

CN108697889B - Systems and methods for preventing, alleviating and/or treating dementia

Info

Publication number: CN108697889B
Application number: CN201680075447.2A
Authority: CN
Inventors: A·J·马托雷尔; C·阿迪埃肯; L-H·蔡; E·布朗; H·亚卡里诺
Original assignee: Massachusetts Institute of Technology
Current assignee: Massachusetts Institute of Technology
Priority date: 2015-11-24
Filing date: 2016-11-23
Publication date: 2022-08-12
Anticipated expiration: 2036-11-23
Also published as: US20200316334A1; IL259533A; US20170143934A1; KR20230161532A; KR102460518B1; AU2021215128A1; AU2021215128B2; KR102603963B1; EP3383482B1; IL283779B; EP3383482A4; JP7204192B2; JP2019502429A; JP2023101026A; US20170304584A1; US10159816B2; CA3003183A1; CN115569282A; IL283779A; EP3383482A1

Abstract

The present disclosure provides methods for preventing, reducing, and treating amyloid-beta (Α β) peptide, C-terminal fragment- β (β -CTF) in a subject by inducing synchronous gamma oscillations in the brain of the subject using a stimulus emitting device that emits a stimulus (e.g., light, sound, and/or touch) at a frequency (e.g., about 40Hz) that synchronously activates a particular cell type (e.g., flash-parvalbumin (FS-PV) immunoreactive interneuron) and/or brain region (e.g., sensory cortex and/or hippocampus) of the subject, for example, in vivo, systems and methods of at least one of levels or changes in at least one of beta-secretase (BACE1), gamma-secretase, neuroinflammation, and/or dementia (e.g., Alzheimer's disease or age-related decline).

Description

Systems and methods for preventing, alleviating and/or treating dementia

Statement of government support

The invention was made with government support under grant number RF1 AG047661 awarded by the national institutes of health. The government has certain rights in the invention.

Cross Reference to Related Applications

In accordance with section 119 (e) of the American code, 35, this application claims priority from U.S. application No. 62/259,187 entitled "System and Methods for presenting, Mitigating, and/or Treating Desentia" filed on 24.11.2015, the disclosure of which is incorporated herein by reference in its entirety.

Technical Field

The present disclosure generally relates to systems and methods for preventing, alleviating, and/or treating dementia in a subject. More particularly, the present disclosure relates to systems and methods for introducing synchronized gamma oscillations into at least one brain region of a subject.

Background

Alzheimer's Disease (AD) is a progressive neurodegenerative disease characterized by memory, orientation, and reasoning decline. It is the most common form of dementia in the world, affecting approximately one-eighth of people over 65 years of age, and is the sixth leading cause of death in the united states. The prevalence of this progressive neurodegenerative disorder is estimated to increase by 40% in the next decade.

Histopathologically, AD can be characterized by the accumulation of amyloid plaques containing amyloid- β (a β) peptide and neurofibrillary tangles made from tau protein. A.beta.peptide is a 36-43 amino acid protein whose normal physiological function is not recognized. A β peptides are formed by sequential proteolytic cleavage of Amyloid Precursor Protein (APP) by β -secretase 1 (BACE1) and γ -secretase. The C-terminal fragment β (β -CTF) is an APP derivative produced during amyloidogenic cleavage of APP by BACE1 and is thus another indicator of A β peptide production. Under normal conditions, soluble a β peptides are produced and secreted by neurons and subsequently cleared from the brain via the cerebrospinal fluid (CSF) pathway. However, in subjects with AD, a β peptides appear to aggregate into higher species to form soluble oligomers and insoluble plaques in a concentration-dependent manner. This aggregation may trigger a number of neurotoxic events, including disturbed brain metabolism, neuroinflammation, reduced functional connectivity, loss of synapses and neurons, and/or formation of NFTs.

A fundamental relationship between a β concentration and neuronal activity has been demonstrated. First, treatment of organotypic hippocampal slices prepared from transgenic (Tg) mice overexpressing APP with tetrodotoxin reduced neuronal activity and subsequently levels of Α β. The opposite effect, increased neuronal activity, was then observed after treatment with picrotoxin. Neuronal activity was also used to demonstrate dynamic regulation of a β peptide concentration and eventual plaque deposition in vivo. In human AD patients, neuroimaging shows that the most severe plaque deposits are likely consistent with the most continuously active brain regions, which is referred to as the "default mode network".

There is currently no cure for AD and treatment options do not inhibit the pathological course of AD, are primarily palliative, and/or may have a variety of worrying side effects. For example, prophylactic and/or therapeutic strategies that target Α β peptides and/or precursors thereof (e.g., Α β immunotherapy and inhibition of β -secretase and γ -secretase) are toxic and/or ineffective in reducing AD lesions in clinical trials. Clinical trials involving amyloid beta vaccines (e.g., bapineuzumab) have failed due to a lack of cognitive benefit. Gamma secretase inhibitors (e.g., semagacetat) fail clinical trials by exacerbating the cognitive deficits of the subject. Even existing drugs like acetylcholinesterase inhibitors (e.g. donepezil and rivastigmine) and N-methyl-D-aspartate (NMDA) -receptor antagonists (e.g. memantine) show only slight cognitive benefits.

SUMMARY

The key microscopic pathological hallmarks of AD are the presence of amyloid plaques, NFTs, and extensive neuronal loss. This accumulation of neuronal insults occurs over a length of time and induces macroscopic circuit dysfunction in the brain, specifically gamma power deficiency during memory and attention tasks. These gamma oscillations (e.g., about 20Hz to about 100Hz, about 20Hz to about 80Hz, or about 20Hz to about 50Hz) primarily elicit and are modulated by flash-parvalbumin (FS-PV) -interneurons.

In one aspect, the present disclosure provides devices, methods and systems for preventing, alleviating and/or treating dementia in a subject comprising inducing synchronized gamma oscillations in at least one brain region of the subject. In some embodiments, the dementia is associated with AD, vascular dementia, frontotemporal dementia, dementia with lewy bodies, and/or age-related cognitive decline. The subject may be a human or an animal.

In one embodiment, the synchronized gamma oscillations have a frequency of about 20Hz to about 50Hz, such as about 40 Hz. The synchronized gamma oscillations can be induced in a cell type specific manner. For example, the oscillation may correspond to a synchronous activation of the FS-PV-interneuron. The synchronized gamma oscillations can be induced in a brain region-specific manner. For example, the oscillations may correspond to a simultaneous activation in at least one of a hippocampus region and a sensory cortex region.

In one embodiment, a method for preventing, alleviating and/or treating dementia in a subject comprises the steps of: controlling a stimulus emission device to emit a stimulus and exposing and/or administering the subject to the stimulus, thereby inducing in vivo synchronized gamma oscillations in at least one brain region of the subject. The stimulus may have a frequency of about 35Hz to about 45Hz, such as a frequency of about 40 Hz. The stimulus emission means may be tactile means, light emitting means and/or sound emitting means. For example, the light emitting device may be a fiber optic device. The duration of exposure and/or administration of the stimulus to the subject may be about one hour. Exposing the subject to the stimulus and/or administering the stimulus to the subject may be repeated over a period of time. For example, exposing the subject to the stimulus and/or administering the stimulus to the subject may be repeated at least once per day over the period of time. The time period may include, but is not limited to, 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, one week, two weeks, three weeks, and/or one month (or longer, such as once per day for the remaining life of the subject).

In one aspect, a method for reducing the level (e.g., amount or ratio) of a β peptide in at least one brain region of a subject comprises inducing synchronous γ oscillations in the at least one brain region of the subject. The a β peptides can include one or more isoforms of a β peptide (e.g., isoform a β) _1-40 Isoform a beta _1-42 And/or isoform a β _1-43 ) Soluble a β peptide and/or insoluble a β peptide.

In some embodiments, the synchronized gamma oscillation reduces production of Α β peptide in the at least one brain region of the subject, e.g., by reducing the level (e.g., amount or ratio) of a C-terminal fragment (CTF) and/or an N-terminal fragment (NTF) of APP in the at least one brain region of the subject. Said synchronized gamma oscillation may reduce cleavage of APP into CTF and NTF by BACE1 and/or gamma-secretase in said at least one brain region of said subject. The synchronized gamma oscillations can reduce the level (e.g., number or ratio) of endosomes in the at least one brain region of the subject. For example, the endosomes can be positive for early endosomal antigen 1(EEA1) and/or the Ras-associated protein encoded by the RAB5A gene (RAB 5). In some embodiments, the synchronized gamma oscillations promote clearance of a β peptide in the at least one brain region of the subject. The synchronized gamma oscillations may increase the uptake of a β peptide by microglia in the at least one region of the subject.

In one aspect, a method for increasing the level (e.g., number or ratio) of microglia in at least one brain region of a subject, a morphological change of the microglia consistent with a neuroprotective state, and/or an activity of the microglia comprises inducing synchronous gamma oscillation in the at least one brain region of the subject. The synchronized gamma oscillations may up-regulate at least one differentially expressed gene involved in the microglial activity in the at least one brain region of the subject, such as Nr4a1, Arc, Npas4, Cd68, B2m, Bsr2, Icam1, Lyz2, Irf7, Spp1, Csf1r, and/or Csf2 ra. The morphological change of the microglia consistent with the neuroprotective state may include an increase in cell body size and/or a decrease in process length.

In one aspect, a method for reducing a level (e.g., amount or ratio) of a β peptide in a hippocampus of a subject includes optogenetically stimulating an FS-PV-interneuron in the hippocampus, the FS-PV-interneuron expressing a optogenetic actuator, with a plurality of light pulses, thereby modulating a period of in vivo synchronized gamma oscillations in an excitation neuron (e.g., FS-PV-interneuron) measured by a local field potential that reduces the level of a β peptide in the hippocampus. The light pulses may have a pulse frequency of about 40 pulses/s. Each light pulse may have a duration of about 1 ms. The at least one light pulse may have a wavelength of about 473 nm. The optogenetic actuator may include channelrhodopsin, halophilic rhodopsin and/or archaerhodopsin. For example, the optogenetic actuator may be channelrhodopsin-2 (ChR 2).

In one aspect, a method for reducing a level (e.g., amount or ratio) of soluble and/or insoluble a β peptides in a visual cortex of a subject comprises stimulating the subject with a plurality of light pulses at a pulse frequency of about 40 pulses/s, thereby inducing in vivo synchronized gamma oscillations in the visual cortex that reduce the level of the soluble and/or insoluble a β peptides in the visual cortex.

In one aspect, a method for reducing the level (e.g., amount or ratio) of tau phosphorylation in a visual cortex of a subject comprises stimulating the subject with a plurality of light pulses at a pulse frequency of about 40 pulses/s, thereby inducing in vivo synchronized gamma oscillations in the visual cortex that reduce tau phosphorylation in the visual cortex.

In one aspect, a method for reducing a level (e.g., an amount or a ratio) of a β peptides in a hippocampus and/or an auditory cortex of a subject comprises stimulating the subject with a plurality of sound pulses at a pulse frequency of about 40 pulses/s, thereby inducing in vivo-synchronized γ -oscillations in at least one of the hippocampus and the auditory cortex that reduce the level of a β peptides in at least one of the hippocampus and the auditory cortex.

In one aspect, a system for preventing, reducing, and/or treating a level (e.g., amount or rate) or change in a β peptide, neuroinflammation, and/or cognitive function in a subject includes a stimulus emission device for synchronized activation in vivo of a brain region of the subject, at least one memory for storing stimulus parameters and processor-executable instructions, and at least one processor communicatively connected to the stimulus emission device and the at least one memory. After executing the processor-executable instructions, the at least one processor controls the stimulus emission device to emit the stimulus according to the stimulus parameters, the parameters including a frequency at which the brain regions are simultaneously activated, whereby the Α β peptide, the neuroinflammation, and/or the dementia of the subject are prevented, reduced, and/or treated. The frequency may be about 35 Hz to about 45Hz, such as about 40 Hz. The in vivo simultaneous activation may be regulated by enzymes and/or occur in specific cell types, such as immunoreactive FS-PV-interneurons. The enzymes may include a optogenetic activator, a microbial opsin, ChR2, and/or the vector AAV-DIO-ChR 2-EYFP.

In one aspect, a system for preventing, reducing and/or treating a level (e.g., amount or ratio) or change in a β peptide, neuroinflammation and/or cognitive function in a subject comprises a light occlusion device for reducing ambient light to at least one eye of the subject and/or a noise cancellation device for reducing ambient noise to at least one ear of the subject. The light occlusion device may comprise a light emitting unit for emitting light stimuli to the at least one eye for in vivo simultaneous activation of at least one of the visual cortex and the hippocampus of the subject. The noise cancellation device may comprise a speaker unit for emitting sound stimuli to the at least one ear for in vivo synchronized activation of at least one of the auditory cortex and hippocampus of the subject. The system also includes at least one memory for storing processor-executable instructions and at least one processor communicatively connected to the optical occlusion device and/or the noise cancellation device and the at least one memory. After executing the processor-executable instructions, the at least one processor may control the light occlusion device such that the light emitting unit emits the light stimulus at a frequency that simultaneously activates at least one of the visual cortex and the hippocampus. Alternatively or additionally, the at least one processor may control the noise cancellation device such that the speaker unit actuates the sound stimulus at the frequency that simultaneously activates at least one of the auditory cortex and the hippocampus at the frequency.

In one aspect, a method for improving cognitive function in a subject includes controlling at least one electroacoustic transducer to convert an electrical audio signal into a corresponding acoustic stimulus. In some embodiments, the sound stimulus comprises a series of clicks having a click frequency of about 35 clicks/s to about 45 clicks/s. The method further comprises exposing the subject to the sound stimulus and/or administering the stimulus to the subject to induce synchronized gamma oscillations in at least one brain region of the subject, the synchronized gamma oscillations causing an improvement in the cognitive function of the subject. The cognitive function may include recognition, discrimination, and/or spatial memory.

In one aspect, a method for preventing, reducing and/or treating a level (e.g., amount or ratio) or change in a β peptide, neuroinflammation and/or cognitive function in a subject comprises controlling at least one electroacoustic transducer to convert an electrical audio signal into a corresponding sound stimulus comprising a series of ticks having a tick frequency of about 35 ticks/s to about 45 ticks/s, and exposing and/or administering the subject to the sound stimulus to induce synchronous gamma oscillations in at least one brain region of the subject that cause the prevention, the reduction and/or the treatment of the level of a β peptide, neuroinflammation and/or dementia in the subject.

The A beta peptide may comprise A beta peptideOf (a) (e.g., isoform a β) _1-40 Isoform a beta _1-42 And/or isoform A beta _1-43 ) Soluble a β peptides and/or insoluble a β peptides. The synchronized gamma oscillations can prevent, reduce and/or treat the level of Α β peptide, neuroinflammation and/or dementia in the subject by increasing the number of microglia in the at least one brain region of the subject and/or enhancing the uptake of Α β peptide by the microglia in the at least one brain region. The at least one brain region may comprise the auditory cortex and/or the hippocampus.

The click frequency may be about 40 clicks/s. Each click in the series of clicks may have a duration of about 1 ms. Each click in the series of clicks may have a frequency of about 10Hz to about 100kHz, about 12Hz to about 28kHz, about 20Hz to about 20kHz, and/or about 2kHz to about 5 kHz. Each click in the series of clicks may have a sound pressure level of about 0dB to about 85dB, about 30dB to about 70dB, and about 60 dB to about 65 dB.

The at least one electroacoustic transducer may comprise at least one earphone, in which case the method may comprise applying the at least one earphone around, on and/or in at least one ear of the subject to direct the sound stimulation into the at least one ear of the subject. The method may also include reducing ambient noise using passive noise isolation and/or active noise cancellation.

In one aspect, a system for preventing, reducing, and/or treating a level (e.g., amount or ratio) or change in a β peptide, neuroinflammation, and/or cognitive function in a subject comprises: at least one electroacoustic transducer for converting an electrical audio signal into a corresponding sound stimulus, the sound stimulus comprising a series of clicks having a click frequency of about 35 clicks/s to about 45 clicks/s; at least one memory device for storing the electrical audio signal and processor-executable instructions; and at least one processor communicatively connected to the at least one electroacoustic transducer and the at least one memory device. After executing the processor-executable instructions, the at least one processor controls the electro-acoustic transducer to output the sound stimulus to at least one ear of the subject to induce synchronous gamma oscillations in at least one brain region of the subject that cause the level of Α β peptides, the prevention, the reduction, and/or the treatment of neuroinflammation and/or dementia in the subject.

The system may be stationary or portable. If the at least one electro-acoustic transducer comprises at least one earphone for the subject to wear around, on and/or in the at least one ear to direct the sound stimulus into the at least one ear of the subject and reduce ambient noise, the system may further comprise an earphone interface for communicating the electrical audio signal to the at least one earphone. Alternatively or additionally, the system may comprise a neuroimaging scanner to monitor function in the at least one brain region of the subject before, during and/or after the output of the sound stimulus.

In one aspect, a method for preventing, reducing and/or treating dementia in a subject comprises providing a device that induces synchronized gamma oscillations in at least one brain region of the subject.

In one aspect, a method for maintaining and/or reducing blood levels (e.g., amounts) of glucocorticoids involved in stress response in a subject includes providing a means for inducing synchronized gamma oscillations in at least one brain region of the subject.

In one aspect, a method for preventing and/or reducing anxiety in a subject comprises providing a device that induces synchronous gamma oscillation in at least one brain region of the subject.

In one aspect, a method for maintaining and/or enhancing memory association includes providing a device that induces synchronous gamma oscillation in at least one brain region of the subject. The memory association may be based on spatial memory.

In one aspect, a method for maintaining and/or enhancing cognitive flexibility includes providing a means for inducing synchronous gamma oscillations in at least one brain region of the subject.

In one aspect, a method for maintaining and/or reducing changes to the anatomy and/or morphology of at least one brain region of a subject includes providing a device that induces synchronous gamma oscillation in the at least one brain region of the subject. The anatomy and/or morphology may include brain weight, lateral ventricle size, thickness of the cortical layer, thickness of the neuronal layer, and/or vessel diameter. The at least one brain region may comprise the visual cortex, somatosensory cortex and/or islet cortex of the subject.

In one aspect, a method for maintaining and/or reducing a change to the number of neurons, the quality of DNA in the neurons, and/or synaptic plaque density (synaptic plaque density) in at least one brain region of a subject comprises providing a device that induces synchronous gamma oscillation in the at least one brain region of the subject. The at least one brain region may comprise the visual cortex, somatosensory cortex, islet cortex, and/or hippocampus of the subject.

In one aspect, a device for inducing synchronized gamma oscillations in at least one brain region of a subject can prevent, reduce and/or treat dementia and/or anxiety in the subject, maintain and/or enhance memory association and/or cognitive mobility in the subject, and/or maintain and/or reduce anatomical, morphological, cellular and molecular changes to the at least one brain region of the subject.

It should be appreciated that all combinations of the foregoing concepts and additional concepts discussed in greater detail below (provided such concepts are not mutually inconsistent) are contemplated as being part of the inventive subject matter disclosed herein. In particular, all combinations of claimed subject matter appearing at the end of this disclosure are contemplated as being part of the inventive subject matter disclosed herein. It is to be understood that the terms explicitly employed herein, which may also appear in any disclosure incorporated by reference, are to be accorded the most consistent meaning with the specific concepts disclosed herein.

Other systems, methods, and features will be or become apparent to one with skill in the art upon examination of the following figures and detailed description. All such additional systems, methods, and features are intended to be included within this description, the scope of the invention, and the protection to be protected by the accompanying claims.

Brief Description of Drawings

Skilled artisans will appreciate that the figures are primarily for illustrative purposes and are not intended to limit the scope of the inventive subject matter described herein. The figures are not necessarily to scale; in some instances, various aspects of the inventive subject matter disclosed herein may be shown exaggerated or enlarged in the drawings to facilitate an understanding of various features. In the drawings, like reference numbers generally refer to, for example, like features (e.g., functionally similar and/or structurally similar elements).

Figure 1 is a schematic diagram showing a mouse running through a virtual linear maze on a spherical treadmill according to some embodiments.

Fig. 2A and 2B are electrical traces recorded from hippocampus CA1 and showing theta oscillations and Sharp Wave Ripple (SWR) according to some embodiments.

Fig. 3A and 3B are graphs showing mean and standard deviation of normalized power spectra and normalized power spectral densities during a time period of θ in march-old Tg 5XFAD mice and Wild Type (WT) mice according to some embodiments.

Fig. 4A and 4B are spectrograms showing SWR of WT mice and 5XFAD mice according to some embodiments.

Fig. 5A-5C are graphs depicting the distribution of instantaneous gamma frequency during SWR according to some embodiments.

Fig. 6A is a series of graphs depicting Z-score gamma power as a function of time since the peak of SWR in 5XFAD and WT mice according to some implementations. Fig. 6B is a graph depicting the cumulative distribution of gamma power during SWR in 5XFAD and WT mice according to some embodiments. Fig. 6C and 6D are graphs depicting cumulative distributions of Z-score gamma power over the course of 100ms around the peak of SWR for WT mice and 5XFAD mice according to some embodiments. Fig. 6E is a graph depicting the cumulative distribution of gamma power during large SWR in 5XFAD and WT mice, according to some embodiments.

Fig. 7A is a graph depicting the fraction of spikes as a function of phase of gamma oscillation, and fig. 7B is a graph depicting the depth of spike modulation during SWR according to some embodiments. Fig. 7C and 7D are graphs showing spike scores as a function of phase of gamma oscillation in hippocampal CA1 during SWR according to some embodiments. Fig. 7E is a graph depicting the fraction of spikes as a function of phase of gamma oscillation, and fig. 7F is a graph depicting the depth of spike modulation during large SWR according to some embodiments.

Fig. 8A and 8B are graphs depicting SWR rate/non-theta time periods in 5XFAD animals and WT animals for each animal and all animals combined, according to some embodiments.

Fig. 9 is a schematic diagram showing viral vectors used to modulate activation of specific cell types in the brain of a subject, according to some embodiments.

Fig. 10A and 10B are schematic diagrams showing the delivery of a signal to the CA1 region of the hippocampus of a subject, according to some embodiments.

Fig. 11 is an immunofluorescence image showing immunostaining of neural tissue of a subject using ChR2 and DAPI, according to some embodiments.

FIG. 12A is an immunofluorescence image displaying ChR2-EYFP expressed in PV + interneurons according to some embodiments. Fig. 12B is a series of immunofluorescence images showing immunohistochemistry using anti-EYFP antibodies and anti-PV antibodies according to some embodiments.

Fig. 13A and 13B include schematic diagrams of studies, electrical traces of local field potentials, and power spectral densities of FS-PV-interneurons according to some embodiments.

Fig. 14A and 14B include raw electrical traces, traces filtered for spikes after optogenetic stimulation, and graphs of the spike likelihood after 1ms laser pulse initiation, according to some embodiments.

Fig. 15A is a bar graph showing the difference in firing rate between a 40-Hz stimulation period and a random stimulation period according to some embodiments. Fig. 15B is a bar graph showing the multi-unit firing rate per 40-Hz stimulation period, random stimulation period, and no stimulation period for each animal, according to some embodiments.

Fig. 16A is an electrical trace recorded from a subject's hippocampus during a frequency-specific increase in stimulation of a particular cell type in the CA1 region of the subject's hippocampus, according to some embodiments. Fig. 16B is a graph showing the frequency-specific increase in power spectral density of local field potential power in stimulation of specific cell types in the CA1 region of the hippocampus of the subject, according to some embodiments.

FIGS. 17A and 17B are graphs depicting relative Abeta of 5XFAD/PV-Cre CA1 obtained by one-way ANOVA according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graph.

FIGS. 18A and 18B are graphs depicting relative Abeta of 5 XFAD/alpha CamKII-Cre CA1 obtained by one-way ANOVA according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graph.

Fig. 19A is a series of images showing immunohistochemistry using an anti- Α β antibody and an anti-EEA 1 antibody in the hippocampal CA1 region, according to some embodiments. Fig. 19B is a series of bar graphs depicting the relative immunoreactivity of a β normalized to EYFP according to some embodiments.

Figure 20A is a series of immunofluorescence images showing immunohistochemistry using anti- Α β antibodies in the hippocampal CA1 region of 5XFAD/PV-Cre according to some embodiments. Fig. 20B is a bar graph depicting the relative immunoreactivity of a β normalized to EYFP according to some embodiments.

Fig. 21A is a representative western blot depicting levels of APP (CT695), APP NTF (a8967), APP CTF (CT695), and β -actin (a5316) (loading control) in CA1, according to some embodiments. Fig. 21B is a bar graph depicting the relative (normalized to actin) immunoreactivity of APP CTF at 40-Hz versus EYFP and random conditions according to some embodiments. Fig. 21C is a series of western blots depicting levels of full-length APP 2106(CT695), APP CTF 2108(CT695), and β -actin 2112 (a5316, load control) in CA1, according to some embodiments.

Fig. 22A is a bar graph depicting the relative (normalized to the agonist protein) immunoreactivity of APP NTF in 40-Hz versus EYFP and randomized conditions according to some embodiments. Fig. 22B is a bar graph depicting the relative (normalized to actin) immunoreactivity of full-length APP in EYFP, random, and 40-Hz conditions according to some embodiments.

Fig. 23 is a series of immunofluorescence images showing immunohistochemistry using anti-Rab 5(ADI-KAp-GP006-E) antibodies according to some embodiments.

Fig. 24A is a bar graph representing the relative immunoreactivity of EEA1 normalized to EYFP, and fig. 24B is a bar graph depicting the relative Rab5 intensity levels of CA1 from 5XFAD/PV-Cre under EYFP, 40Hz, and random stimulation conditions, according to some embodiments.

Fig. 25A is a graph depicting a β peptide isoform a β after different types of stimulation of the CA1 region of the hippocampus of a subject, according to some embodiments _1-40 Horizontal bar graph of (2). Fig. 25B is a graph depicting the a β peptide isoform a β after stimulation of a particular cell type in the CA1 region of the hippocampus of a subject using gamma oscillation, according to some embodiments _1-42 Reduced bar graph of (2). Fig. 25C is a series of images showing a decrease in the level of CTF (e.g., β -CTF) and an increase in the level of full-length APP (normalized to actin) following stimulation of a particular cell type in the CA1 region of the hippocampus of a subject using gamma shaking, according to some embodiments.

Fig. 26A-26B are immunofluorescence images showing endosome levels (based on EEA1 levels) after different types of stimulation of the CA1 region of the hippocampus of a subject, according to some embodiments.

Fig. 27 is a bar graph depicting mean intensity values (normalized to FAD) for the immunofluorescence images of fig. 6A-6B after different types of stimulation of the CA1 region of the hippocampus of the subject, according to some embodiments.

Fig. 28 is a heat map presenting differentially expressed genes determined by whole transcriptome ribonucleic acid sequencing (RNA-seq) of the mouse hippocampal CA1 region with and without 40-Hz stimulation, according to some embodiments.

Figure 29 is a box plot showing FPKM values for up-and down-regulated genes in EYFP and 40-Hz conditions according to some embodiments.

Figure 30 is a pie chart showing cell type-specific expression patterns of up-regulated genes identified after 40-Hz stimulation according to some embodiments.

Fig. 31 is a bar graph showing RT-qPCR validation of specific gene targets in RNA-seq datasets, according to some embodiments.

Fig. 32A and 32B are graphs showing the power spectral density of local field potentials recorded above the brain during a 40-Hz light scintillation performance according to some embodiments.

Fig. 33 is a bar graph depicting RT-qPCR validation of specific gene targets in RNA-seq datasets, according to some embodiments.

FIG. 34 is a series of immunofluorescence images showing immunohistochemistry using anti-Iba 1 (019-.

Fig. 35A is a bar graph depicting the number of microglia in EYFP and 40-Hz conditions according to some embodiments. Figure 35B is a bar graph depicting the diameter of microglia cell bodies normalized to EYFP in EYFP, 40-Hz, and random stimulation conditions according to some embodiments. Figure 35C is a bar graph depicting the average length of microglia primary processes normalized to EYFP in EYFP, 40-Hz, and random stimulation conditions, according to some embodiments. FIG. 35D is a bar graph depicting the percentage of Iba 1-positive (microglia) cell bodies that were also A β -positive in EYFP and 40-Hz stimulation conditions, according to some embodiments.

Fig. 36 is a series of 3D renderings formed by merging the immunofluorescence images from fig. 34, according to some embodiments.

Figure 37A is a series of immunofluorescence images showing immunohistochemistry using Hoechst in the hippocampal CA1 region of 5XFAD/PV-Cre according to some embodiments. Figure 37B is a bar graph depicting estimated CA1 thickness of 5XFAD/PV-Cre in EYFP and 40-Hz stimulation conditions according to some embodiments.

FIG. 38A is a heatmap showing Differentially Expressed Genes (DEG) determined by whole genome RNA-seq of hippocampal CA1 following 40-Hz FS-PV + stimulation or control stimulation according to some embodiments. Figure 38B is a graph showing overlap between DEG upregulated in the tree condition in figure 38A, according to some implementations.

Fig. 39 is a bar graph depicting RT-qPCR validation of specific gene targets in the RNA-seq dataset of fig. 38A, according to some embodiments.

Fig. 40 is a diagram showing biological processes to which the upregulated genes of fig. 38A are associated, according to some embodiments.

Fig. 41 is a diagram showing biological processes to which the down-regulated genes of fig. 38A are associated, according to some embodiments.

Fig. 42A is a series of immunofluorescence images showing levels of Iba1 after different types of stimulation of the CA1 area of the hippocampus of the subject, according to some embodiments. Fig. 42B is a bar graph depicting mean intensity values for the immunofluorescence image of fig. 42A, according to some embodiments.

Figure 43A is a schematic showing a mouse exposed to a light scintillation stimulus, according to some embodiments. Fig. 43B includes plots of local field potential traces and power spectral density in the visual cortex before and during 40-Hz light blinking in accordance with some embodiments. 43C-43F are graphs depicting power spectral densities of local field potentials in the visual cortex according to some embodiments.

Fig. 44A is a series of histograms depicting the fraction of spikes in the visual cortex as a function of time for four cycles and an equivalent time period of random light flicker for 40-Hz light flicker, according to some embodiments. Fig. 44B is a series of electrical traces of local field potentials recorded above the brain during light blinking according to some embodiments.

Fig. 45A is a bar graph showing the difference in firing rate between 40-Hz light flashes and random light flashes, according to some embodiments. Fig. 45B is a graph showing multiple unit firing rates in the visual cortex according to some embodiments.

Fig. 46A is a schematic diagram showing an experimental example according to some embodiments. Fig. 46B-46C are diagrams that respectively further show a β peptide isoform a β after the experimental paradigm of fig. 46A according to some embodiments _1-40 And Abeta _1-42 A graph of changes in baseline levels of (a).

Fig. 47A and 47B are illustrations depicting, respectively, a β in a 5XFAD visual cortex, according to some embodiments _1-40 And Abeta _1-42 Bar graph of changes in baseline level of (a).

FIG. 48A is a graph depicting A β in 5XFAD tubal cortex under dark and 40-Hz scintillation conditions according to some embodiments _1-40 And Abeta _1-42 Bar graph of changes in baseline level of (a). FIG. 48B is a graph depicting A β in APP/PS1 visual cortex under dark and 40-Hz glint conditions according to some embodiments _1-40 And Abeta _1-42 Bar graph of changes in baseline level of (a). FIG. 48C is a graph depicting A β in WT visual cortex under dark and 40-Hz glint conditions, according to some embodiments _1-40 And Abeta _1-42 Bar graph of changes in baseline level of (a).

FIG. 49 is a series of immunofluorescence images showing immunohistochemistry using anti-Iba 1 (019-.

Fig. 50A is a bar graph depicting the number of Iba 1-positive cells (microglia) according to some embodiments. Figure 50B is a bar graph depicting the diameter of microglia cell bodies normalized to control under dark and 40-Hz blinking conditions according to some embodiments. Figure 50C is a bar graph depicting the average length of primary processes of microglia normalized to control under dark and 40-Hz blinking conditions, according to some embodiments. Figure 50D is a bar graph depicting the percentage of microglia that are also Α β -positive under dark and 40-Hz blinking conditions, according to some embodiments.

Figure 51 is a series of 3D renderings (from immunofluorescence images) of Iba + microglia under dark and 40-Hz scintillation conditions from class-treated 100 μm tissue sections according to some embodiments. Clarity is a method of making brain tissue transparent using, for example, acrylamide-based hydrogels that are built from within and attached to tissue.

Fig. 52A is a flow diagram showing a method for isolating microglia from visual cortex using Fluorescence Activated Cell Sorting (FACS), according to some embodiments. Figure 52B is a graph depicting a β in microglia cells isolated from the visual cortex of march-old 5XFAD and WT control animals using the method of figure 52A, according to some embodiments _1-40 Horizontal bar graph.

Figure 53A is a series of immunofluorescence images demonstrating immunohistochemistry using SVP38 antibody to detect synaptic vesicle proteins in a march-old 5XFAD visual cortex under dark and 40-Hz scintillation conditions according to some embodiments. Fig. 53B is a bar graph depicting relative SVP38 intensity levels of 5XFAD visual cortex after dark and 40-Hz light flicker conditions according to some embodiments.

Figure 54A is a graph showing a β peptide isoform a β after stimulation of the visual cortex of a subject using gamma oscillation, according to some embodiments _1-42 Reduced bar graph of (2). Figure 54B is a graph showing the a β peptide isoform a β once again after stimulation of the visual cortex of a subject with gamma oscillation and twenty-four hours after stimulation, according to some embodiments _1-42 Horizontal bar graph of (2).

Fig. 55A includes plots of electrical traces and power spectral density of local field potentials in a hippocampus before and during 40-Hz light blinking, according to some embodiments. Fig. 55B is a series of histograms of spike scores in hippocampus as a function of time for random light flashes for four cycles and an equivalent time period, respectively, of 40-Hz light flashes, according to some embodiments.

Fig. 56A is a bar graph showing the difference in firing rate between 40-Hz light flashes and random light flashes, according to some embodiments. Fig. 56B is a graph showing the multi-cell firing rate in CA1 during 40-Hz light blinking according to some embodiments.

FIG. 57A isDepicting relative Α β in 5XFAD visual cortex according to some embodiments _1-40 Horizontal bar graph. Figure 57B is a graph depicting relative Α β in 5XFAD visual cortex according to some embodiments _1-42 Horizontal bar graph.

FIG. 58A is a graph depicting relative Abeta in a 5XFAD visual cortex with recovery after 40-Hz light flicker conditions, according to some embodiments _1-40 Horizontal bar graph. FIG. 58B is a graph depicting relative Abeta in a 5XFAD visual cortex with recovery after 40-Hz light blinking, according to some embodiments _1-42 Horizontal bar graph.

Fig. 59A is a schematic diagram showing a study according to some embodiments. FIG. 59B is a graph depicting relative Abeta in the visual cortex of a sixty-month-old 5XFAD mouse after seven days of one hour/day under dark or 40-Hz blinking conditions, according to some embodiments _1-42 Horizontal bar graph. FIG. 59C is a graph showing relative Abeta in the visual cortex of a sixty-month-old 5XFAD mouse after seven days of one hour/day under dark or 40-Hz blinking conditions, according to some embodiments _1-40 Horizontal bar graph.

Figure 60A is a series of immunofluorescence images showing immunohistochemistry using Α β antibodies in the visual cortex of june-old 5XFAD mice after seven days of one hour/day under dark or 40-Hz scintillation conditions, according to some embodiments. Figure 60B is a bar graph depicting the number of Α β -positive plaque deposits in the visual cortex of a june-large 5XFAD mouse after seven days of one hour/day under dark or 40-Hz blinking conditions, according to some embodiments. Figure 60C is a bar graph depicting the area of Α β -positive plaques in the visual cortex of a june-large 5XFAD mouse after seven days of one hour/day under dark or 40-Hz blinking conditions, according to some embodiments.

Fig. 61A is a series of immunofluorescence images showing immunohistochemistry using anti-phosphorylated Tau (S202) antibody and anti-MAP 2 antibody in april-sized P301S mice after seven days of one hour/day under dark or 40-Hz scintillation conditions, according to some embodiments. Fig. 61B is a bar graph depicting relative phosphorylated tau (ptau) (S202) intensity levels of the visual cortex of P301S after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments. Fig. 61C is a bar graph depicting relative MAP2 intensity levels of the P301S visual cortex after seven days of one hour/day under dark and 40-Hz light scintillation conditions, according to some embodiments.

Fig. 62A is a series of immunofluorescence images showing immunohistochemistry using anti-pTau 6202(S404) antibody in 4 month old P301S mice after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments. FIG. 62B is a bar graph depicting relative pTau (S400/T403/S404) fluorescence intensity levels of P301S visual cortex after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments.

Fig. 63A is a series of immunofluorescence images showing immunohistochemistry using anti-pTau 6302(S396) antibody in april-sized P301S mice after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments. Fig. 63B is a bar graph depicting the relative pTau (S396) fluorescence intensity levels of the P301S visual cortex after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments.

Fig. 64 is a series of immunofluorescence images showing immunohistochemistry using anti-Iba 1 antibody in april-sized P301S mice after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments.

Fig. 65A is a bar graph depicting the number of microglia after seven days of one hour/day under dark and 40-Hz light scintillation conditions, according to some embodiments. Figure 65B is a bar graph depicting the diameter of microglia cell bodies normalized to a control after seven days of one hour/day under dark and 40-Hz blinking conditions, according to some embodiments. Figure 65C is a bar graph depicting the average length of primary processes of microglia normalized to a control after seven days of one hour/day under dark and 40-Hz blinking conditions, according to some embodiments.

Figure 66 is a graph showing soluble and insoluble a β peptide isoforms a β in the visual cortex of a subject with and without visual gamma stimulation, according to some embodiments _1-40 And Abeta _1-42 A graph of the level of (c).

Fig. 67A-67B are graphs showing whole brain Α β peptide levels in subjects with and without transcranial gamma stimulation, according to some embodiments.

Fig. 68A is a flow diagram showing a study conducted to examine whether gamma exposure and/or administration according to some embodiments results in stress to a subject. Fig. 68B is a bar graph depicting levels of corticosterone indicative of stress response in a subject.

Fig. 69A is a flow diagram showing a study conducted to examine whether gamma exposure and/or administration according to some embodiments reduces anxiety in a subject. Fig. 69B is an image showing an elevated plus labyrinth device. Fig. 69C and 69D are images showing representative trajectories of subjects during an elevated plus maze session.

Figure 70 is a bar graph depicting the average time a subject spends exploring the open and closed arms during an elevated plus maze session.

Figure 71A is a flow diagram showing a study conducted to examine whether gamma exposure and/or administration according to some embodiments reduces stress and/or anxiety in a subject. Fig. 71B is an image showing an open field site. Fig. 71C and 71D are images showing representative trajectories of subjects during open field testing.

Fig. 72A is a graph depicting the average amount of time a subject spends in the center of an open field during each minute of an open field test. Figure 72B is a bar graph depicting the average total time spent by the edges of the open field of a subject during the open field test.

Fig. 73A and 73B are schematic diagrams showing the implementation of checking whether gamma exposure and/or administration according to some embodiments alters the subject's inherent novelty seeking behavior. Fig. 73C is a bar graph depicting the average amount of time a subject spends exploring a first novel item compared to a second novel item according to the schematic of fig. 73A.

Fig. 74 is a graph depicting the average amount of time a subject spends exploring a novel item during each minute according to the schematic of fig. 73B.

Figure 75A is a flow diagram showing a study conducted using the fear conditioning paradigm to examine whether gamma exposure and/or administration affects learning and memory of a subject according to some embodiments. Fig. 75B is a stimulus diagram showing a tone test with changing environments as a function of time.

Fig. 76A and 76B are bar graphs demonstrating enhanced memory of subjects according to some embodiments.

Fig. 77A is a flow diagram showing a study performed to examine whether gamma exposure and/or administration according to some embodiments improves a subject's memory. FIG. 77B is a diagram of a Morris water maze showing hidden platforms in target quadrants. Fig. 77C and 77D are images showing representative trajectories of subjects during the Morris water maze detection test.

Fig. 78A is a graph depicting the average amount of time a subject spends on a platform hidden in the Morris water maze test found each day. Fig. 78B is a graph depicting the average amount of time the subject spent looking for a removed platform in the target quadrant during each half minute. Fig. 78C is a graph depicting the average amount of time the subject spent looking for a removed platform in the opposite quadrant during each half minute.

FIG. 79A is a graph showing the Morris water maze test hiding the platform in the first quadrant. FIG. 79B is a graph showing the Morris water maze test for hidden platforms in the second quadrant (opposite the first quadrant) for reverse learning. Fig. 79C is a graph depicting the average amount of time a subject spends on a platform hidden in the discovery Morris water maze reverse learning test per day.

Figure 80A is a flow diagram showing a study conducted to examine whether chronic gamma exposure and/or administration affects spatial learning and memory in a subject according to some embodiments. Figure 80B is a graph depicting the average amount of time a subject spends on the platform hidden in the Morris water maze test found each day. Figure 80C is a bar graph depicting the average amount of time a subject spends looking for a removed platform in the target quadrant during a thirty second trial.

FIG. 81A is a flow chart showing the study of FIG. 80A extended to include reverse learning. Figure 81B is a graph depicting the average amount of time a subject spends on a platform hidden in the discovery Morris water maze reverse learning test each day.

Figure 82A is a bar graph depicting the average amount of time a subject spends looking for a removed platform in the target quadrant during a thirty second trial. Fig. 82B is a bar graph depicting the average amount of time the subject spent looking for a removed platform in the opposite quadrant.

Fig. 83 is a time line graph of a study conducted to examine the effect of gamma exposure and/or administration on deoxyribonucleic acid (DNA) damage and neuronal loss in the visual cortex of a subject, according to some embodiments.

Figure 84 is a diagram showing a group of subjects for conducting a study to examine the effects of gamma exposure and/or administration according to some embodiments.

Fig. 85 is a bar graph of large brain weight variation across the group of subjects of fig. 84, according to some embodiments.

Fig. 86 is a bar graph comparing fold change in lateral ventricle dilation across a group of subjects of fig. 84, according to some embodiments.

Fig. 87A-87E are images showing lateral ventricles of a group representing the subject of fig. 84, according to some embodiments.

Fig. 88A-88C are diagrams illustrating brain anatomy of a brain region of interest, according to some embodiments.

Fig. 89 is a bar graph depicting the average thickness of V1-cortical layers across the group of subjects of fig. 84, according to some embodiments.

Fig. 90 is a bar graph depicting the average thickness of the V1-NeuN-positive cell layer across the group of subjects of fig. 84, according to some embodiments.

Fig. 91A-91E are images showing cells with Hoechst markers and/or NeuN markers representing the group of subjects of fig. 84, according to some embodiments.

Fig. 92 is a bar graph depicting the average thickness of SS 1-cortical layer across the group of subjects of fig. 84, according to some embodiments.

Fig. 93 is a bar graph depicting the average thickness of layers of SS 1-NeuN-positive cells across the group of subjects of fig. 84, according to some embodiments.

Fig. 94A-94E are images showing cells with Hoechst labeling and/or NeuN labeling across a group of subjects of fig. 84, according to some embodiments.

Fig. 95 is a bar graph depicting the average thickness of the cortical layer across the island cortex of the group of subjects of fig. 84, according to some embodiments.

Fig. 96 is a bar graph depicting the average thickness of the NeuN-positive cell layer across the islet cortex of the group of subjects of fig. 84, according to some embodiments.

Fig. 97A-97E are images showing cells with Hoechst markers and/or NeuN markers representing a group of subjects of fig. 84, according to some embodiments.

Fig. 98 is a bar graph comparing the amount of visual cortex NeuN-positive cells across a group of subjects of fig. 84, according to some embodiments.

Fig. 99 is a bar graph comparing the amount of visual cortical γ H2 AX-positive cells across a group of subjects of fig. 84, according to some embodiments.

Figure 100 is a series of images showing a visual cortex sample representative of the group of subjects of figure 84 according to some embodiments.

Fig. 101 is a bar graph comparing the amount of somatosensory cortex NeuN-positive cells across a group of subjects of fig. 84, according to some embodiments.

Fig. 102 is a bar graph comparing the amount of somatosensory cortical γ H2 AX-positive cells across a group of subjects of fig. 84, according to some embodiments.

Fig. 103 is a series of images showing a somatosensory cortex sample representative of the group of subjects of fig. 84 according to some embodiments.

Figure 104 is a bar graph comparing the amount of island cortex NeuN-positive cells across the group of subjects of figure 84, according to some embodiments.

Fig. 105 is a bar graph comparing the amount of islet cortex γ H2 AX-positive cells across a group of subjects of fig. 84, according to some embodiments.

Fig. 106 is a series of images showing an island cortex sample representative of the group of subjects of fig. 84, according to some embodiments.

Fig. 107 is a bar graph comparing the amount of hippocampus NeuN-positive cells across a group of subjects of fig. 84, according to some embodiments.

Fig. 108 is a bar graph comparing the amount of hippocampus gamma H2 AX-positive cells across a group of subjects of fig. 84, according to some embodiments.

Fig. 109 is a series of images showing hippocampus samples representing a group of subjects of fig. 84, according to some embodiments.

Figure 110 is a bar graph comparing visual cortical stain density across a group of subjects of figure 84, according to some embodiments.

Fig. 111 is a bar graph comparing somatosensory cortical stain density across a group of subjects of fig. 84, according to some embodiments.

Fig. 112 is a bar graph comparing island cortex stain density across a group of subjects of fig. 84, according to some embodiments.

Fig. 113A-113D are images showing Hoechst stain, VGluT1 marker, and/or GAD65 marker in a representative sample, according to some embodiments. Fig. 113E and 113F are images showing methods of stain quantification according to some embodiments.

Fig. 114 is a stimulation diagram showing click train stimulation according to some embodiments.

Figure 115 is a flowchart showing a study conducted to examine whether auditory gamma exposure and/or administration induces microglial activation in the auditory cortex of a subject according to some embodiments.

Figure 116A is a bar graph depicting the average number of microglia in the auditory cortex of a subject, according to some embodiments. Figure 116B is a bar graph depicting fold changes in microglial process length in the auditory cortex of a subject according to some embodiments.

Fig. 117A and 117B are representative images of microglia in the auditory cortex of a subject according to some embodiments.

Fig. 118A and 118B are magnified images of the microglia protrusion length from fig. 117A and 117B, according to some embodiments.

Figures 119A and 119B are magnified images of microglia cell body size from figures 117A and 117B according to some embodiments.

Figure 120A is a bar graph depicting the average number of microglia/image field in the auditory cortex of a subject according to some embodiments. Figure 120B is a bar graph depicting the mean fold change in cell size of microglia in the auditory cortex of a subject according to some embodiments.

Fig. 121A and 121B are representative images of microglia in an auditory cortex of a subject according to some embodiments.

Fig. 122A-122D are graphs depicting soluble a β isoform a β in the auditory cortex and hippocampus of a subject, according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graph of (2).

Fig. 123A-123D are graphs depicting insoluble Α β isoforms in the auditory cortex and hippocampus of subjects, according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graph of (2).

Fig. 124A-124D are representative images of microglia in the auditory cortex of a subject according to some embodiments.

FIG. 125A is a flow chart showing a novel item identification test. Fig. 125B is a bar graph demonstrating memory improvement according to some embodiments.

FIG. 126A is a flow chart showing a novel item location test. Fig. 126B is a bar graph demonstrating memory and/or discrimination improvement according to some embodiments.

Fig. 127A is a graph depicting the average amount of time a subject spends on a platform hidden in the Morris water maze test found each day. Figure 127B is a bar graph depicting the average amount of time a subject spent looking for a removed platform in the target quadrant during a probing test.

Fig. 128A is a series of representative immunofluorescence images showing enlarged vasculature in the visual cortex according to some embodiments. Fig. 128B is a bar graph depicting blood vessel diameter in the visual cortex and showing the increase in blood vessel diameter after gamma exposure according to some embodiments.

Detailed Description

In one aspect, the present disclosure provides methods, devices, and systems for preventing, alleviating, and/or treating a brain disorder or cognitive dysfunction/deficit in a subject. In some embodiments, the brain disorder is dementia.

Cognitive function depends primarily on neural network activity related to attention and working memory, specifically the precise timing of oscillations of gamma frequency (rhythms (e.g., about 20Hz to about 100Hz, about 20Hz to about 80Hz, or about 20Hz to about 50 Hz)). Because these oscillations arise from synaptic activity, they provide a direct correlation between the molecular properties of neurons and higher levels of coherent brain activity. Importantly, gamma oscillatory activity is disrupted in the neuropathic damaged neural circuits through AD and may represent a key determinant of memory impairment in the disease. It has not been determined whether a causal relationship exists between a lesion and a disturbance of brain oscillations. However, driving brain rhythms can serve as a multi-target therapy for treating dementia, such as AD, and can be achieved through non-invasive therapy.

In one aspect, the present disclosure provides devices, methods, and systems for enhancing or inducing gamma oscillation. In some embodiments, the enhancing or inducing gamma oscillation is performed by a optogenetic method. In other embodiments, the enhancement or induction of gamma oscillation is performed by a behavioral method. The present disclosure provides for the enhancement and/or induction of gamma oscillation by optogenetic, behavioral, or other means to reduce AD lesions.

In one aspect, the present disclosure provides devices, systems, and methods for restoring or inducing a gamma oscillatory rhythm in a subject suffering from dementia. In some embodiments, the dementia is AD, vascular dementia, frontotemporal dementia (FTD), and/or dementia with lewy bodies. Thus, in some embodiments, the present disclosure provides devices, systems, and methods for treating dementia.

As used herein, the term "treatment" refers to both therapeutic treatment and preventative or prophylactic measures. In some embodiments, subjects in need of treatment include those already with the disease or condition as well as those who are likely to develop the disease or condition and whose purpose is to prevent, delay, or attenuate the disease or condition. For example, in some embodiments, the devices, methods, and systems disclosed herein may be employed to prevent, delay, or attenuate a subject's genetically predisposed disease or condition, such as AD. In some embodiments, the devices, methods, and systems disclosed herein may be employed to treat, alleviate, reduce the symptoms of, and/or delay the progression of a disease or condition that a subject has been diagnosed with, such as AD.

As used herein, the term "subject" means a mammal, such as a rodent, feline, canine, or primate. Preferably, the subject according to the invention is a human.

As used herein, the term "about" refers to plus or minus ten percent of the subject modified by "about".

Dementia is a condition characterized by loss of intellectual ability and/or memory impairment. Dementia includes, for example, AD, vascular dementia, dementia with lewy bodies, Pick's disease, frontotemporal dementia (FTD), AIDS dementia, age-related cognitive disorders, and age-related memory disorders. Dementia may also be associated with neurological and/or psychiatric conditions, such as, for example, brain tumors, brain lesions, epilepsy, multiple sclerosis, Down's syndrome, Rett's syndrome, progressive supranuclear palsy, frontal lobe syndrome, schizophrenia, and traumatic brain injury.

AD is the most common neurodegenerative disease in developed countries. Histopathologically, AD is characterized by the accumulation of amyloid plaques containing the a β peptide and NFTs made from tau protein. Clinically, AD is associated with progressive cognitive impairment characterized by loss of memory, function, language ability, judgment, and executive function. AD often causes severe behavioral symptoms in its later stages.

Vascular dementia may also be referred to as cerebrovascular dementia and refers to cerebrovascular disease (e.g., infarction of the cerebral hemisphere) which typically has a fluctuating course of time periods that improve and progressively worsen. Vascular dementia may include one or more symptoms of disorientation, impaired memory, and/or impaired judgment. Vascular dementia can result from discrete multiple infarcts or other vascular causes including, for example, autoimmune vasculitis, such as that found in systemic lupus erythematosus; infectious vasculitis, such as Lyme's disease; recurrent intracerebral hemorrhage; and/or stroke.

Frontotemporal dementia (FTD) is a progressive neurodegenerative disorder. Subjects with FTD often exhibit marked behavioral and character changes, often accompanied by language disorders.

Dementia with lewy bodies is characterized by: developing one or more symptoms of dementia having features that overlap with features of AD; the development of Parkinson's disease (Parkinson's disease); and/or early development of hallucinations. Dementia with lewy bodies is generally characterized by daily fluctuations in the severity of symptoms.

In some aspects, the present disclosure provides methods for preventing, alleviating, and/or treating dementia in a subject comprising inducing synchronized gamma oscillations in the brain of the subject. In some embodiments, the induction of gamma oscillation in a subject having a neurological disease or disorder or age-related decline restores a gamma oscillation rhythm disrupted in the subject by or associated with the disease or disorder or age-related decline.

In some embodiments, inducing gamma oscillation reduces isoform a β _1-40 And Abeta _1-42 And (4) generating. In some embodiments, inducing gamma oscillation enhances clearance of a β (e.g., isoform a β) from the brain of the subject _1-40 And Abeta _1-42 ). In some embodiments, inducing gamma oscillation prevents accumulation of a β in the brain of the subject. In some embodiments, the methods provided herein reduce the level of a β in the brain of the subject by about 10%, about 20%, about 30% relative to the level of a β in the brain of the subject prior to treatmentAbout 40%, about 50%, about 60%, about 70%, or more. In some embodiments, the level of a β in the brain of the subject is reduced by at least about 50% relative to the level of a β in the brain of the subject prior to treatment.

In some embodiments, the level of a β in the brain of the subject is reduced by reducing clearance of APP in the brain of the subject. In some embodiments, the methods provided herein reduce clearance of APP in the brain of the subject by about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, or more, relative to the level of APP clearance in the brain of the subject prior to treatment. In some embodiments, the level of APP clearance in the brain of the subject is reduced by at least about 50% relative to the level of APP clearance in the brain of the subject prior to treatment. In some embodiments, the level of APP clearance is measured by the level of C-terminal fragment β (β -CTF) in the brain of the subject. In some embodiments, the level of APP clearance in the brain is reduced via inhibition of β -secretase and/or γ -secretase (such as by increasing the level of inhibition of β -secretase and/or γ -secretase activity). In some embodiments, the methods provided herein reduce aggregation of a β plaques in the brain of the subject.

In some embodiments, the method improves cognitive ability and/or memory in the subject.

In another aspect, the present disclosure provides a method for inducing a neuroprotective feature or a neuroprotective environment in the brain of a subject, comprising inducing synchronized gamma oscillations in the brain of the subject. For example, in some embodiments, the neuroprotective characteristic is associated with a neuroprotective microglia characteristic. In additional embodiments, the neuroprotective characteristic is induced by or associated with increasing the activity of the M-CSF pathway. In some embodiments, the neuroprotective environment is associated with an anti-inflammatory signaling pathway. For example, in some embodiments, the anti-inflammatory signaling pathway is an anti-inflammatory microglia signaling pathway.

In some embodiments, the neuroprotective characteristic is associated with a decrease or absence of pro-inflammatory glial cell activity. Proinflammatory glial cell activity is associated with the M1 phenotype of microglia and includes the production of Reactive Oxygen Species (ROS), the neurosecretory protein chromogranin a, the secreted cofactor cystatin C, NADPH oxidase, nitric oxide synthase enzymes such as iNOS, NF- κ B-dependent inflammatory response protein, and proinflammatory cytokines and chemokines (e.g., TNF, IL-1 β, IL-6, and IFN γ).

In contrast, the M2 phenotype of microglia is associated with down-regulation of inflammation and repair of inflammation-induced injury. Anti-inflammatory cytokines and chemokines (IL-4, IL-13, IL-10 and/or TGF β) as well as increased phagocytic activity are associated with the M2 phenotype. Thus, in some embodiments, the methods provided herein elicit the neuroprotective M2 phenotype of microglia. In some embodiments, the methods provided herein increase phagocytic activity in the brain of a subject. For example, in some embodiments, the methods provided herein increase phagocytic activity of microglia, such that clearance of a β is increased.

The gamma oscillations may comprise about 20Hz to about 100 Hz. Thus, in some embodiments, the present disclosure provides methods for preventing, alleviating, or treating dementia in a subject comprising inducing gamma oscillations in the brain of the subject of about 20Hz to about 100Hz, or about 20Hz to about 80Hz, or about 20Hz to about 50Hz, or about 30Hz to about 60Hz, or about 35Hz to about 45Hz, or about 40 Hz. Preferably, the gamma oscillation is about 40 Hz.

The stimulus may comprise any detectable change in the internal or external environment of the subject that directly or ultimately induces gamma oscillation in at least one brain region. For example, the stimulus may be designed to stimulate electromagnetic radiation receptors (e.g., photoreceptors, infrared receptors, and/or ultraviolet receptors), mechanoreceptors (e.g., mechanical stress and/or strain), nociceptors (i.e., pain), vocal receptors, electrical receptors (e.g., electric fields), magnetic receptors (e.g., magnetic fields), hydrogen receptors, chemoreceptors, heat receptors, olfactory receptors, and/or proprioceptors (i.e., position sensing). The absolute threshold or minimum amount of sensation required to elicit a response from a receptor may vary based on the type of stimulus and the subject. In some embodiments, the stimulation is adjusted based on the individual's sensitivity.

In some embodiments, the gamma oscillations are induced in a brain region-specific manner. For example, in some embodiments, the gamma oscillations are induced in the hippocampus, visual cortex, tubal cortex, auditory cortex, or any combination thereof. By way of example, in some embodiments, gamma oscillations are induced in the visual cortex using glints; and in other embodiments, gamma oscillations are induced in the auditory cortex using auditory stimuli at specific frequencies. In some embodiments, gamma oscillations are induced simultaneously in multiple brain regions using a combination of visual, auditory, and/or other stimuli. In some embodiments, the gamma oscillations are induced in a virtual reality system.

In some embodiments, the subject receives stimulation through an environment configured to induce gamma oscillation, such as a chamber that passively or actively blocks non-relevant stimulation (e.g., light blocking or noise cancellation). Alternatively or additionally, the subject may receive stimulation through a system that includes, for example, light blocking or noise cancelling aspects. In some embodiments, the subject receives the visual stimulus through a stimulus emitting device (such as eyewear designed to deliver the stimulus). The device may block out other light. In some embodiments, the subject receives auditory stimulation through a stimulation emitting device (such as an earpiece designed to deliver the stimulation). The device may eliminate other noise.

In addition to at least one interface for emitting stimulation, some embodiments may include at least one processor (for, e.g., generating stimulation, controlling the emission of stimulation, monitoring the emission/outcome of stimulation, and/or processing feedback regarding stimulation/outcome), at least one memory (for storing, e.g., processor-executable instructions, at least one stimulation, stimulation generation strategies, feedback, and/or outcomes), at least one communication interface (for communicating with, e.g., a subject, a health care provider, a caregiver, a clinical research investigator, a database, a monitoring application, etc.), and/or a detection device (for detecting and providing feedback regarding, e.g., a stimulus and/or the subject, including whether gamma oscillations are induced, subject sensitivity, cognitive function, physical or chemical changes, stress, safety, etc.).

In some embodiments, the gamma oscillations are induced by visual stimuli (such as flashing light at about 20Hz to about 100 Hz). In a particular embodiment, the gamma oscillations are induced by a flash of light at about 20Hz to about 50 Hz. In further embodiments, the gamma oscillations are induced by a flash of light at about 35Hz to about 45 Hz. In yet further embodiments, the gamma oscillations are induced by a flash of light at about 40 Hz. In some embodiments, the subject receives (e.g., is placed in a chamber with a light blocking device or wears a light blocking device that emits) about 20Hz to about 100Hz flash, or about 20Hz to about 50Hz flash or about 35Hz to about 45Hz flash, or about 40Hz flash.

In some embodiments, the gamma oscillations are induced by auditory stimuli, such as sound at a frequency of about 20Hz to about 100Hz, or about 20Hz to about 80Hz, or about 20Hz to about 50Hz, or about 35Hz to about 45Hz, or about 40 Hz. In some embodiments, the subject receives (e.g., is placed in a room with or wears a noise cancellation device that emits) auditory stimuli of about 20Hz to about 100Hz, about 20Hz to about 80Hz, about 20Hz to about 50Hz, about 35Hz to about 45Hz, about 40 Hz.

In some embodiments, the subject receives (e.g., is placed in a chamber with a light blocking device or wears a light blocking device that emits) visual and/or auditory stimuli for about one hour, about 2 hours, about 3 hours, about 4 hours, about 5 hours, or more. In some embodiments, the subject receives (e.g., is placed in a chamber with a light blocking device or wears a light blocking device, which device emits) stimulation for no more than about 6 hours, no more than about 5 hours, no more than about 4 hours, no more than about 3 hours, no more than about 2 hours, or no more than about one hour. In some embodiments, the subject receives (e.g., is placed in a chamber with a light blocking device or wears a light blocking device, which emits) stimulation for less than one hour.

In some embodiments, the subject is subjected to the methods provided herein. In other embodiments, the subject is undergoing treatment for a plurality of separate situations using the methods provided herein. The subject may be treated according to a routine schedule or when symptoms appear or worsen. In some embodiments, chronic treatment may be effective in reducing soluble a β peptide and/or insoluble a β peptide (i.e., plaques).

In some embodiments, the gamma oscillation is induced in a cell type specific manner. In some embodiments, the gamma oscillations are induced in FS-PV-interneurons. When used to describe a class of neurons, the term "flash" (FS) refers to the ability of a neuron to discharge at high rates with little spike frequency modulation or spike height decay for long periods of time. Thus, these neurons are capable of sustained high frequency (e.g., equal to or greater than about 100Hz or about 150Hz) firing without significant modulation. This property of FS neurons can be largely attributed to their expression of fast-delaying rectifying channels (in other words, channels that are activated and deactivated very quickly).

In one aspect, the stimulation may be non-invasive. As used herein, the term "non-invasive" refers to devices, methods, and systems that do not require surgical intervention or manipulation of the body (such as injection or implantation of a composition or device). For example, the stimulus may be visual (e.g., flashing light), acoustic (e.g., acoustic vibration), and/or tactile (mechanical stimulus using force, vibration, or movement).

In another aspect, the stimulation may be invasive or at least partially invasive. For example, visual, acoustic, and/or tactile stimulation may be combined with injection or implantation of a composition (e.g., a light-sensitive protein) or device (e.g., an integrated fiber optic and solid state light source).

Experimental data

Gamma oscillations were reduced during hippocampal SWR in early-diseased 5XFAD mice.

Gamma deficiency has been observed in multiple brain regions for several neurological and psychiatric disorders, including a reduction in spontaneous gamma synchrony in human patients with AD. Interestingly, reduced spontaneous γ was also found in two mouse models of AD in vivo (human amyloid precursor protein (hAPP) Tg mice and apolipoprotein E4 allele (APOE4) knock-in mice) and in vitro sectioning studies of another mouse model (Tg CRND8 mice). However, it is unclear whether gamma oscillation is altered in other mouse models of AD, whether it occurs early in disease progression, and whether gamma destruction affects disease progression.

To address these issues, neural activity from conscious-behaving 5XFAD mice (a well-established model of AD carrying five familial AD mutations) was recorded. Specifically, the 5XFAD mouse expressed five different familial AD alleles, including APP KM670/671NL (sweden), APP I716V (florida), APP V717I (london), PSEN 1M 146L (a > C), and PSEN 1L 286V. Thus, 5XFAD mice were used as a model for AD amyloidosis. In some embodiments, neural activity is recorded from mice that are about 3 months of age (at which time the mice have elevated levels of a β), but prior to the onset of major plaque accumulation and the manifestation of learning and memory deficits. Figure 1 is a schematic diagram showing a mouse running through a virtual linear maze on a spherical treadmill according to some embodiments. Food-restricted mice may receive rewards by running back and forth on a spherical treadmill through a virtual linear maze.

Neural activity from hippocampal subregions CA1 can be recorded. Fig. 2A and 2B are electrical traces recorded from hippocampus CA1 and showing theta oscillations and Sharp Wave Ripple (SWR) according to some embodiments. In some embodiments, gamma oscillations in CA1 may be present during different periods of activity, such as during running when theta oscillations (4-12 Hz) are observed, as shown in fig. 2A, and during static and exploratory behavior when SWR occurs, as shown in fig. 2B.

The power spectral density during theta oscillations was examined and no significant difference was found in the slow gamma power (20Hz to 50Hz range) of 5XFAD mice and WT littermates. Fig. 3A and 3B are graphs showing mean and standard deviation of normalized power spectra and normalized power spectral densities during a θ time period in march-old Tg 5XFAD and WT mice according to some embodiments. Fig. 3A shows the mean and standard deviation of normalized power spectra over the θ time period in march-old 5XFAD (n ═ 6 mice) and WT (n ═ 6 mice) mice. In some embodiments, the power spectral density of each animal may be normalized to its peak (in θ). Fig. 3B shows the normalized power spectral density over the θ time period in march-old 5XFAD (n ═ 6 mice) and WT (n ═ 6 mice) mice.

In some embodiments, as a next step, gamma oscillations during SWR are examined, which are high frequency oscillations of 150-250Hz lasting about 50-100 ms. SWR is associated with an outbreak of group activity (during which the pattern of spike activity replays across the hippocampus). Previous work has shown that slow γ rises during SWR and synchronizes across CA3 and CA 1. Therefore, neurons spanning these hippocampal subregions are more likely to fire together during SWR, as neurons are more likely to fire a phase locked to γ. A study was conducted in which SWRs (defined as the time periods in which the power in the ripple bands from about 150Hz to about 250Hz was above the mean by more than four standard deviations) were identified and the frequency spectra were plotted to examine the power across a range of frequencies during these SWRs. In the spectrogram, an increased power above 100Hz indicating a high frequency oscillation characteristic of SWR and a concurrently increased power below about 50Hz indicating gamma power may be observed.

Fig. 4A and 4B are spectrograms showing SWR of WT mice and 5XFAD mice according to some embodiments. Fig. 4A shows a spectrum plot of the average SWR trigger for one WT mouse showing an increase in the gamma band 402 with frequencies below 80Hz during SWR 404, magnified in the right panel. Figure 4B shows the mean SWR triggered spectrum of one 5XFAD mouse showing an increase in the gamma band during SWR, although this increase is lower than in the WT mice shown in figure 4A.

In some embodiments, the study found that the instantaneous frequency of these slower oscillations (10-50Hz range, as further described herein) was a unimodal distribution centered around 40 Hz. Fig. 5A-5C are graphs depicting the distribution of instantaneous gamma frequency during SWR according to some embodiments. Fig. 5A shows the distribution of instantaneous γ frequencies during SWR (n-370 SWR) for the same mouse with peaks around 40Hz shown in fig. 4A. Fig. 5B shows the distribution of instantaneous γ frequencies during SWR in 5XFAD and WT mice showing the distribution around 40Hz for each recording session, and fig. 5C shows the mean and Standard Error (SEM) of the mean across animals (

n

820, 800, 679, 38, 1875, 57 γ cycles/sessions in six 5XFAD animals, and n 181, 1075, 919, 1622, 51, 1860, 1903 γ cycles/sessions in six WT animals).

In some embodiments, these gamma oscillations during SWR in WT mice were then compared to those in 5XFAD littermate mice, and defects in gamma during SWR were found: while gamma power did increase from baseline during SWR in 5XFAD mice, gamma power during SWR was significantly less in 5XFAD mice than in WT mice, as further described herein.

Fig. 6A is a series of graphs depicting z-score gamma power as a function of time since the peak of SWR in 5XFAD and WT mice, respectively, according to some implementations. Fig. 6A shows the mean and SEM and shows the increase in gamma power over the course of SWR relative to baseline.

Fig. 6B is a graph depicting the cumulative distribution of gamma power during SWR in 5XFAD and WT mice according to some embodiments. The cumulative distribution of gamma power during SWR showed significantly less increase in 5XFAD mice than in WT mice (rank sum test, p)<10 ^-5 (ii) a N 2166 SWRs in six 5XFAD mice, and n 3085 SWRs in six WT mice; the median z-score was 1.02(0.39-1.87, 25-75 th percentile) in 5XFAD mice and 1.18(0.53-2.15, 25-75 th percentile) in WT mice.

Fig. 6C and 6D are graphs depicting the cumulative distribution of z-score gamma power over the course of 100ms around the peak of SWR, as well as the mean and SEM (shaded) across animals for WT mice 606 and 5XFAD mice 608 according to some embodiments (n 514, 358, 430, 22, 805, 37 SWR/sessions in six 5XFAD animals, and n 82, 311, 370, 776, 18, 710, 818 SWR/sessions in six WT animals).

Figure 6E is a graph depicting the cumulative distribution of z-score gamma power during 100ms around the peak of a large SWR (detection threshold greater than 6 standard deviations above the mean) in WT mice 614 and 5XFAD mice 616, according to some embodiments. Rank sum testing is performed on the non-normally distributed data population as further described herein. Figure 6E shows a significantly smaller increase in WT mice 614 and 5XFAD mice 616 (rank sum test, p)<10 ^-5 N-1000 SWRs in six 5XFAD mice and n-1467 SWRs in six WT mice).

In some embodiments, the spikes are phase modulated by these gamma oscillations in both groups, however modulation of the spikes by gamma phase is weaker in 5XFAD animals than in WT animals. The study found that the depth of modulation can be significantly less in 5XFAD animals than in WT animals.

Fig. 7A is a graph depicting spike fraction as a function of phase of gamma oscillation, and fig. 7B is a graph depicting depth of spike modulation during SWR as a function of gamma phase during SWR in march-old 5XFAD (n-6 mice) and WT (n-6 mice) mice according to some embodiments (rank sum test, bootstrap resampling, p-phase) < 10 ^-5 This is important when the controls were run for multiple comparisons, with n being 2500 sharp peaks-gamma phase distributions of 5XFAD and 3000 WT distributions, a median depth of modulation of 0.35 in 5XFAD mice (0.21-0.44, 25 th-75 th percentile), and 0.38 in WT mice (0.29-0.47, 25 th-75 th percentile). Error bars indicate mean +/-SEM. Plot 704 shows a frequency plot of the depth of spike modulation

Fig. 7C and 7D are graphs showing peak scores in hippocampal CA1 as a function of phase of gamma oscillations during SWR and mean values and SEM across animals for each animal in 5XFAD animals and WT animals (n 2475, 1060, 3092, 25, 6521, 123 spikes/sessions during SWR in six 5XFAD animals, and

n

360, 4741, 1564, 2961, 88, 3058, 4270 spikes/sessions during SWR in six WT animals) according to some embodiments.

Fig. 7E is a graph depicting spike fraction as a function of phase of gamma oscillation, and fig. 7F is a graph depicting the depth of spike modulation during large SWR (detection threshold above mean greater than 6 standard deviations, as described further herein) in march's 5XFAD (n-6 mice) and WT (n-6 mice) (and rank test, botstrap resampling, one asterisk indicating p <10 ^-10 N-2500 sharp XFAD-gamma phase distributions and 3000 WT distributions). Error bars indicate mean +/-SEM.

The study also found that there may be fewer SWRs/times in 5XFAD mice in the non-theta period compared to WT (rank and test, p)<10 ^-5 In six 5XFAD mice n 634 non-theta time periods and in six WT mice n 750 non-theta time periods, the median value in 5XFAD mice is 0.07Hz (0-0.17, 25 th-75 th percentile) and the median value in WT mice is 0.12Hz (0-0.24, 25 th-75 th percentile)), thereby further reducing the time period of gamma power rise as disclosed above.

Fig. 8A and 8B are graphs depicting SWR rate/non-theta time periods in 5XFAD mice 802 and WT mice 804 (rank sum test, p) for each animal (fig. 8A) and all animals combined, according to some embodiments<10 ^-10 N is 117, 210, 151, 55, 100, 1 non-theta periods/session in six 5XFAD animals and 80, 68, 115, 95, 15, 159, 218 non-theta periods/sessions in six WT animals). These results reveal the defect of modulation of gamma oscillations and the peak of hippocampal CA1 in a mouse model of AD prior to the development of major amyloid plaque accumulation, as well as evidence of cognitive deficits.

Optogenetic stimulation of FS-PV-interneurons at gamma frequency drives gamma oscillations in the CA1 region of the hippocampus.

Early disease progression in this mouse model of AD observed gamma deficiency during SWR causes the following problems: whether gamma oscillation can affect molecular and cellular AD pathophysiology. To test this problem, gamma oscillations were driven optogenetically by expressing ChR2 in a Cre-dependent manner using a bilaterally defined inverted open reading frame (DIO) ChR2-EYFP adenovirus-associated virus (AAV) in FS-PV-interneuron in hippocampal CA1 of 2.5 month old 5XFAD/PV-Cre double transgenic mice. A study was conducted to determine whether genetic induction of hippocampal gamma oscillations in mice affects molecular lesions in a mouse model of AD. Hippocampal gamma oscillations were genetically induced in wakeful behavioural WT mice and 5XFAD mice.

Adeno-associated virus (i.e., AAV5 virus) was generated with a bilaterally defined reverse open reading frame (DIO) ChR2 linked to an Enhanced Yellow Fluorescent Protein (EYFP) driven by the EF1 alpha promoter. Fig. 9 is a schematic diagram showing a viral vector (i.e., AAV5-DIO-ChR2-EYFP) for modulating activation of a particular cell type in the brain of a subject, according to some embodiments. Viral expression was targeted to the CA1 region of hippocampus in a cell-type specific manner. In the presence of Cre-recombinase, one of the two incompatible loxP variants flips to achieve expression of ChR 2.

The CA1 region of the hippocampus of 5XFAD mice was infected with AAV-DIO-ChR2-EYFP or EYFP-only constructs using a stereotactic virus injection method that allows precise regional targeting of viral infection. In one embodiment, at the time of injection, the cannula containing the fiber optic cable (white rod) is placed about 0.3mm above the targeted brain region. After two weeks (which provides time for mouse recovery and viral expression in PV cells), CA1 interneurons were optogenetically manipulated.

Fig. 10A and 10B are schematic diagrams showing the delivery of a signal to the CA1 region of the hippocampus of a subject, according to some embodiments. In fig. 10A, mice running through the maze on the ball while undergoing stimulation by optogenetics in the hippocampus are shown, according to some embodiments. As shown in fig. 10A and 10B, arrow 1000 indicates blue light blinking at about 40Hz to activate brain regions.

In the described embodiment, a 200-mW 493-nm DPSS laser was connected to a patch cord at each end using a fibre channel/physical contact connector. During the course of the experiment, about 1mW of optical stimulation was delivered for about one hour. More specifically, blue light (e.g., 473nm) is delivered randomly at various frequencies, including θ (e.g., about 8Hz), γ (e.g., about 40Hz), and also at about 40Hz, through an optical fiber positioned just above the CA1 region of the hippocampus. In some embodiments, the stimulation conditions are not tested. According to some embodiments, the theta condition serves as a frequency control, and the random condition is controlled for rhythmicity specificity.

After one hour of stimulation was complete, brain tissue was dissected and frozen at-80 ℃ for staining and enzyme-linked immunosorbent assay (ELISA) analysis. Fig. 11 is an immunofluorescence image showing immunostaining of neural tissue of a subject using ChR2 and DAPI, according to some embodiments. In the example, fig. 11 shows DAPI (nuclear) and ChR2 staining in hippocampus.

FIG. 12A is an immunofluorescence image displaying ChR2-EYFP expressed in PV + interneurons according to some embodiments. Fig. 12A shows that ChR2-EYFP is strongly expressed in PV + interneurons in CA1 of march-old 5XFAD/PV-Cre mice (scale bar 100 μm). FIG. 12B is a series of immunofluorescence images showing immunohistochemistry with anti-EYFP antibodies and anti-PV antibodies in March's 5XFAD/PV-Cre CA1 expressing AAV DIO ChR2-EYFP (which shows EYFP expression only in PV + cells). To compare 5XFAD mice with WT mice, ChR2 was expressed in FS-PV-interneuron in 5XFAD negative littermates. As a control for non-specific effects of light stimulation, 5XFAD/PV-Cre double transgenic mice expressing AAV-DIO containing only EYFP were used. In these mice, light delivery did not cause optogenetic stimulation under the same genetic background and light delivery conditions. In some embodiments, the FS-PV-interneuron at 40Hz is selected for two reasons. First, previous studies have shown that driving FS-PV-interneurons at 40Hz produces the largest LFP response. Second, in some embodiments, gamma defects during SWR are found and the instantaneous gamma frequency during SWR forms a distribution centered around 40Hz, as shown in fig. 5A-5C. In some embodiments, for electrophysiological recording, the time period of 40-Hz stimulation is interleaved with time periods of no stimulation or time periods with stimulation delivered at random intervals (selected from poisson distribution centered at 40 Hz), as further described herein.

Fig. 13A and 13B include schematic diagrams of studies, electrical traces of local field potentials, and power spectral densities of FS-PV-interneurons according to some embodiments. Referring to fig. 13A, 1302 is an electrical trace of the local field potential in CA1 before and during 40Hz optogenetic driving of FS-PV-interneurons. Graph 1304 shows the mean and standard deviation of the power spectral density of FS-PV-interneurons in CA1 during 40-Hz stimulation, random stimulation (stimulation at random intervals with poisson distribution selected from centered at 40 Hz), or no stimulation (n ═ four 5XFAD mice and three WT mice). Figure 13B shows the power spectral density of FS-PV-interneuron in CA1 for each mouse during 40-Hz stimulation 1306, random stimulation 1308, or no stimulation 1310 (n-four 5XFAD mice in the case of 169, 130, 240, 73 40Hz stimulations, 143, 129, 150, 72 random stimulations, and 278, 380, 52, 215 no stimulation periods/animal; and n-three WT mice in the case of 65, 93, 91 40Hz stimulations, 64, 93, 90 random stimulations, and 187, 276, 270 no stimulation). Delivering a 1ms 473-nm light pulse at 40Hz causes increased power at 40Hz in the LFP, as shown in graph 1306 of FIGS. 13A and 13B, while random stimulation does not cause increased power at 40-Hz, as shown in graph 1308 of FIGS. 13A and 13B.

Furthermore, in some embodiments, the light pulses effectively drive spikes 2-3ms after light initiation, and spikes/pulses are similar in both random and 40-Hz conditions. Fig. 14A and 14B include raw electrical traces, traces filtered for spikes after optogenetic stimulation, and graphs of the spike likelihood after 1ms laser pulse initiation, according to some embodiments. Fig. 14A shows an exemplary original trace 1402 and a trace filtered for spike (300-. Graph 1408 shows the frequency profile of spikes/pulses after 1ms laser pulse initiation during 40-Hz stimulation, random stimulation, or no stimulation (n ═ 345762 40-Hz stimulation, 301559 random pulse stimulation, and 32350 no stimulation times, at a distance of 552 40-Hz stimulation, 543 random stimulation, and 1681 no stimulation time periods of at least 500ms in four 5XFAD mice and three WT mice). Fig. 14B shows the spike probability after 1ms laser pulse initiation in response to 40-Hz stimulation 1412, random stimulation 1414, or no stimulation 1410, with approximately 2-3ms spikes increasing after laser pulse initiation (n ═ four 5 XFADs with 87, 130, 8, 73 40-Hz stimulations, 85, 129, 5, 72 random stimulations, and 251, 379, 15, 215 no-stimulation periods/animal; and n ═ three WT with 65, 93, 91 40-Hz stimulation periods/animal, 64, 93, 90 random stimulation periods/animal, and 187, 277, 270 no-stimulation periods/animal). Error bars show mean +/-SEM.

Thus, the 40-Hz oscillations in CA1 are effectively driven by optogenetic stimulation of FS-PV-interneurons. Previous studies have shown that Α β peptide levels are elevated after increased neural activity and reduced after silencing of neural activity. In some embodiments, random stimulation conditions are used to control for the overall change in spike activity caused by stimulation. In some embodiments, the multi-unit firing rates during the staggered periods of 40Hz stimulation and random stimulation are compared, and no significant difference is found between firing rates in these conditions.

Fig. 15A is a bar graph showing the difference in firing rate between a 40-Hz stimulation period and a random stimulation period according to some embodiments. Fig. 15A shows that both types of stimulation elicit a similar amount of spiking activity (Wilcoxon signed rank test for zero median, p)>0.6, n-538 stimulation sessions from four 5XFAD mice and three WT mice, "n.s." indicates not significant). Wilcoxon signed rank test, p, for zero median of difference distribution between firing rates during 40Hz stimulation and random stimulation for all mice together>0.6: median value-1.75X 10 ^-5 Hz (-1.28-1.18Hz, 25 th-75 th percentile) n is 538 stimulation sessions.

Figure 15B is a rank sum test, p-sum test, for bar graphs showing multiple unit firing rate/40-Hz stimulation 1512, random stimulation 1514, and time periods without stimulation 1510 per animal (three WT mice and four 5XFAD mice)>0.09, median valueAnd quartiles are shown in the figure, n-87, 130, 8, 65, 93, 91, 73 stimulation periods at 40-Hz and 85, 129, 5, 64, 93, 90, 72 random stimulation periods per mouse). Boxes show median (white line in box) and quartile (top and bottom of box). The firing rate between 40Hz stimulation and random stimulation was not significantly different in all animals, showing that random stimulation conditions served as a control of spiking activity (rank sum test, p for each animal (three WT mice and four 5XFAD mice))>0.09, median and quartile shown in the figure, n ═ 87, 130, 8, 65, 93, 91, 73 stimulation periods at 40-Hz and 85, 129, 5, 64, 93, 90, 72 random stimulation periods per mouse). It was also examined whether 40-Hz stimulation resulted in too strong activity of neurons relative to no stimulation. In most animals, the firing rate between 40Hz stimulation or random stimulation and no stimulation was not significantly different (rank sum test, p for each animal (2 WT and two 5 XFADs)) >0.25, n-8, 93, 91, 73 40-Hz stimulation periods and 15, 277, 270, 215 baseline periods/animal), or a firing rate during 40Hz stimulation or random stimulation that is lower than the firing rate during no stimulation (rank sum test for each animal (1 WT and 15 XFAD), p-f and p-f, respectively)<10 ^-5 This was significant when corrected for performing multiple comparisons, n-130, 65 40-Hz stimulation periods and 379, 187 baseline periods/animal), indicating that 40-Hz stimulation did not result in too strong neuronal activity. In one animal, there was significantly more activity than during baseline in the case of 40Hz stimulation or random stimulation (rank sum test against 1 mouse of 5XFAD, p)<10 ^-5 N-87 40-Hz stimulation periods and 251 baseline periods per animal). Thus, in six out of seven animals, there was no evidence that 40Hz optogenetic stimulation of FS-PV-interneurons resulted in too strong activity. Thus, in some embodiments, while the random condition does not induce gamma oscillation, it does cause a similar amount of multi-unit spike activity, as shown in fig. 15A.

Fig. 16A is an electrical trace recorded from a subject's hippocampus during a frequency-specific increase in stimulation of a particular cell type in the CA1 region of the subject's hippocampus, according to some embodiments. More specifically, figure 16A is recorded from the hippocampus of the subject during frequency-specific increases in stimulation of FS-PV + (i.e., gamma conditions), according to some embodiments.

Fig. 16B is a graph showing the frequency-specific increase in power spectral density of local field potential power in stimulation of specific cell types in the CA1 region of the hippocampus of the subject, according to some embodiments. In particular, the power spectral density map in fig. 16B verifies the specificity of the stimulation. When FS-PV + is activated by a 40-Hz blue light pulse, the Local Field Potential (LFP) power is enhanced only in the 40Hz band 1600 during gamma stimulation conditions (n ═ 4 mice/group). Neither baseline nor random stimulation conditions showed enhancement at this frequency 1600.

Gamma stimulation reduces a β production in the CA1 region of the hippocampus.

The accumulation of a β can trigger a variety of neurotoxic events typical of AD lesions. Thus, in some embodiments, gamma stimulation affects the overall Α β peptide levels in the 5XFAD mice examined. March-old mice were used, as plaques were not present in these mice in the hippocampus at this stage, allowing soluble a β kinetics to be investigated independent of plaque burden. In some embodiments, it was found that in the CA1 region of hippocampus, one hour stimulation of FS-PV-interneuron resulted in Α β stimulation in the 40Hz group compared to the EYFP control group _1-40 Reduced 53.22% and caused A beta _1-42 A reduction of 44.62%, as measured by a β ELISA assay.

Figures 17A and 17B are relative Α β profiles depicting 5XFAD/PV-Cre CA1 obtained by one-way ANOVA grouping all mice together according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graph (for A β) _1-40 N-8 EYFP and 740Hz mice for A β _1-42 And n is 4 mice/group). The bar graph in FIG. 17A represents the relative A β of 5XFAD/PV-Cre CA1 in each stimulation condition _1-40 And (4) horizontal. Circles 1702 superimposed on the bars in the bar graph indicate individual data points in each group (n-8 EYFP5XFAD/PV-Cre mice, n-7 40-Hz 5XFAD/PV-Cre mice, n-4 8-Hz 5XFAD/PV-Cre mice, n-6Randomized 5XFAD/PV-Cre mice/group). The symbol "n.s." 1704 indicates non-salient, the asterisk 1706 indicates p<0.05, double asterisk 1708 indicates p<0.01, in this figure by one-way ANOVA for all the bars. FIG. 17B represents the relative A β of 5XFAD/PV-Cre CA1 in each stimulation condition _1-42 Levels (n-4 EYFP mice, n-4 40-Hz mice, n-3 8Hz mice, n-3 randomized 5XFAD/PV-Cre mice/group). Fig. 17A and 17B show the mean values and SEM.

Table 1 (below) depicts significantly different raw concentration (pg/ml) values, p, when comparing mice from the same littermate mice receiving different conditions <0.05, by Student's t-test. Table 1 shows the raw a β for each experimental group at ELISA dilution _1-40 And Abeta _1-42 And (4) horizontal.

TABLE 1

In some embodiments, a comprehensive set of control experiments is performed to determine whether the effect is specific for frequency, cell type, and/or rhythmicity. To determine frequency specificity, FS-PV-interneurons of 5XFAD/PV-Cre bispecific mice were driven at 8Hz and no change in Α β levels was observed. The FS-PV-interneurons are then driven at random and the effect is specific to rhythmic stimulation. In fact, amyloid levels were not reduced following random stimulation and, in fact, a β was present _1-40 Instead, 230.1% increase and Abeta _1-42 An increase of 133.8% (see, e.g., FIG. 17A and FIG. 17B, p)<0.01, all mice were grouped together by one-way ANOVALine for A β _1-40 N-8 EYFP mice and n-4 randomized mice for Α β _1-42 And n is 3 mice/group. Mice from the same littermate mice receiving different conditions were compared and a significant difference was observed, p<0.01, by Student's t-test).

Finally, 5XFAD/α CamKII-Cre bispecific mice were used to test the cell type specificity of the effect by stimulation in CamKII + excitatory neurons in hippocampal CA1 at 8Hz and 40 Hz. FIGS. 18A and 18B are graphs depicting relative Abeta of 5 XFAD/alpha CamKII-Cre CA1 obtained by one-way ANOVA according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graph. FIG. 18A represents the relative Abeta of 5 XFAD/alpha CamKII-Cre CA1 in each stimulation condition _1-40 And (4) horizontal. Circles 1802 superimposed on the bars in the bar graph indicate individual data points in each group (n ═ 6 40-Hz 5XFAD/α CamKII-Cre mice, n ═ 3 8-Hz 5XFAD/α CamKII-Cre mice, n ═ 3 random 5XFAD/α CamKII-Cre mice/group, the symbol "n.s." 1804 indicates non-significant, the asterisk 1806 indicates p<0.001, by one-way ANOVA).

FIG. 18B represents the relative Abeta of 5 XFAD/alpha CamKII-Cre CA1 in each stimulation condition _1-42 Levels (n-3 α CamKII-Cre mice/group). In some embodiments, it was found that driving CamKII + excitatory neurons at 8Hz or 40Hz did not produce Α β _1-40 And Abeta _1-42 Significant difference in levels (see, e.g., FIG. 18A and FIG. 18B, right, p>0.05 by one-way ANOVA, n ═ 6 mice at 40Hz and 3 mice at 8Hz (a β) _1-40 ) N-3 mice/group (a β) _1-42 ). If mice from the same littermate mouse that received different conditions are compared, they are not significantly different, p>0.05, by Student's t-test). Similar to the 5XFAD/PV-Cre mice, the use of random stimulation to drive CamKII + neurons also caused A β _1-40 257.6% increase and A β _1-42 133.3% increase (see, e.g., FIG. 18A and FIG. 18B, right, p<0.001 by one-way ANOVA for A β _1-40 N-5 40Hz mice and 3 random mice for a β _1-42 And n is 3 mice/group.A.beta.if mice from the same littermate mouse that received different conditions were compared _1-40 Is significantly different, p<0.001, by Student's t-test, and A β _1-42 Is significantly different, p is 0.13, by Student's t-test).

Thus, the decrease in A β peptide levels after 40-Hz stimulation may be specific for driving FS-PV-interneurons. In some embodiments, to confirm these ELISA findings using immunohistochemistry, Α β -labeling was performed using β -amyloid C-terminal end-specific antibodies that do not cross-react with APP in CA 1.

Fig. 19A is a series of images showing immunohistochemistry using an anti- Α β antibody and an anti-EEA 1 antibody in the hippocampal CA1 region, according to some embodiments. Specifically, fig. 19A is a series of immunofluorescence images (scale bar 50 μm) showing immunohistochemistry using anti- Α β 1902(D54D2) and anti-EEA 11904 (610457) antibodies in the hippocampal CA1 region of 5XFAD/PV-Cre in EYFP, 40-Hz and randomized stimulation conditions. Fig. 19B is a series of bar graphs depicting the relative immunoreactivity of a β normalized to EYFP according to some embodiments. Specifically, fig. 19B shows the relative immunoreactivity of Α β normalized to EYFP (n ═ 4 mice/group, 1908 indicates p <0.05 and 1920 indicates p <0.01, by one-way ANOVA).

Figure 20A is a series of immunofluorescence images showing immunohistochemistry using anti- Α β antibodies in the hippocampal CA1 region of 5XFAD/PV-Cre according to some embodiments. Specifically, fig. 20A is a series of immunofluorescence images (scale bar 50 μm) showing immunohistochemistry using anti- Α β 2002(12F4) antibody in the hippocampal CA1 region of 5XFAD/PV-Cre in EYFP, 40-Hz, and random stimulation conditions. Fig. 20B is a bar graph depicting the relative immunoreactivity of a β normalized to EYFP according to some embodiments. Specifically, fig. 20B shows the relative immunoreactivity of Α β normalized to EYFP (n ═ 4 mice/group, 2004 indicated p <0.05 and 2006 indicated p <0.001, by one-way ANOVA). When compared to the EYFP group, the intensity of Α β -tagging decreased 39.5% after 40-Hz stimulation of FS-PV-interneuron and significantly increased 187.0% after randomized stimulation in march-old 5XFAD/PV-Cre double transgenic mice (see, e.g., figure 19A, figure 19B, figure 20A and figure 20B, p <0.05 and p <0.01, by one-way ANOVA, n ═ 4 mice/group).

Cerebral amyloid concentration may depend on the rate of a β production and clearance. In some embodiments, a β peptides are produced by sequential proteolytic cleavage of APP by β -secretase and γ -secretase. When BACE1 cleaves APP whole protein, CTF and NTF of APP can be generated. In some embodiments, to elucidate how 40-Hz stimulation reduces Α β levels, gamma-affected cleavage of APP was examined by measuring the levels of the cleavage intermediates of APP, CTF and NTF, after FS-PV-interneuron stimulation. After 40-Hz stimulation, CTF was found to be significantly reduced by 18.6% after 40-Hz stimulation and by 19.7% compared to the random group (p <0.05 and p <0.01, by one-way ANOVA, n ═ 6 mice/group) compared to the EYFP group.

Fig. 21A is a representative western blot depicting levels of APP (CT695), APP NTF (a8967), APP CTF (CT695), and β -actin (a5316) (load control) in CA1 in EYFP, random, and 40-Hz stimulation conditions, one mouse/lane, with two biological replicates per condition, according to some embodiments. Fig. 21B is a bar graph depicting the relative immunoreactivity of APP CTFs according to some embodiments. Specifically, fig. 21B shows the relative (normalized to actin) immunoreactivity of APP CTF at 40-Hz versus EYFP and randomized conditions (n ═ 6 mice/group, one asterisk 2102 indicates p <0.05, and two asterisks 2104 indicate p <0.01, by one-way ANOVA). Fig. 21C is a series of western blots depicting levels of full-length APP 2106(CT695), APP CTF 2108(CT695), and β -actin 2112(a5316, load control) in CA1, according to some embodiments. Specifically, figure 21C shows the levels of full-length APP 2106(CT695), APP CTF 2108(CT695), and β -actin 2112(a5316, load control) in CA1 in EYFP, random, and 40-Hz stimulation conditions, one mouse/lane, with two biological replicates per condition.

Fig. 22A is a bar graph depicting relative (normalized to actin) immunoreactivity of APP NTF in 40-Hz versus EYFP and random conditions (n-6 mice/group, symbol "n.s" 2204 indicates non-significant, and 2202 indicates p <0.05, by one-way ANOVA). Figure 22B is a bar graph depicting the relative (normalized to actin) immunoreactivity of full-length APP in EYFP, randomized, and 40-Hz conditions (n-6 mice/group, by one-way ANOVA).

In some embodiments, APP NTF levels were found to be significantly reduced by 28.5% compared to EYFP group and 28.2% compared to random group after 40-Hz stimulation (see, e.g., fig. 21A, fig. 22A and fig. 21C, p <0.05, by one-way ANOVA, n ═ 6 mice/group). Furthermore, the levels of full-length APP in each group appeared similar, showing that the decrease in a β was not due to changes in precursor levels (see, e.g., fig. 21A, fig. 22B, fig. 21C, where n ═ 6 mice/group in APP experiments). In some embodiments, changes in full-length APP may be difficult to detect due to the relatively high abundance of APP compared to its cleavage product in this mouse model.

In some embodiments, treatment of APP occurs within the vesicle trafficking pathway, and previous work has shown that APP is transported into the circulating endosome following active stimulation. Furthermore, enlarged early endosomes have been observed in brain tissue from AD patients and in human neurons derived from AD patients. In some embodiments, to test whether gamma stimulation affects endosomal abundance in experimental animals, early endosomes were characterized in CA1 after 40Hz stimulation and random stimulation using two markers, EEA1 (early endosomal antigen 1) and Rab5 (Ras related protein encoded by the Rab5A gene). Figure 23 is a series of immunofluorescence images (scale bar 50 μm) showing immunohistochemistry in march-old 5XFAD/PV-Cre mice using anti-Rab 5 (ADI-KAp-GP006-E) antibody in EYFP, 40-Hz, and random stimulation conditions.

Figure 24A is a bar graph representing the relative immunoreactivity of EEA1 normalized to EYFP according to some embodiments (n ═ 4 mice/group, one asterisk 2402 indicates p <0.05, and two asterisks 2402 indicate p <0.01, by one-way ANOVA). Figure 24B is a bar graph depicting relative Rab5 intensity levels of CA1 from 5XFAD/PV-Cre under EYFP, 40-Hz, and randomized stimulation conditions according to some embodiments (n ═ 3 mice/group, three asterisks 2408 indicate p <0.001, by one-way ANOVA). In some embodiments, EEA1 staining produces punctate cytoplasmic and juxtamembrane patterns in neuronal cell bodies that are typical for early endosomes (see, e.g., fig. 19A). In some embodiments, Rab5 labeling is primarily restricted to the cell body and plasma membrane, represented by small thin colored spots concentrated within the endosomal and membrane compartments (see, e.g., fig. 23). In summary, early endosomal markers of CA1 neurons demonstrated a significant decrease in EEA1 (39.7%) and Rab5 (40.1%) staining intensity following 40-Hz stimulation compared to EYFP controls (see, e.g., figure 19A, figure 23, figure 24A, p <0.05 and p <0.001, by one-way ANOVA, n ═ 2 sections from 3 mice/group). In contrast, randomized stimulation of FS-PV-interneurons increased EEA1 staining intensity by 122% compared to EYFP controls (see, e.g., fig. 19A and fig. 24A, p <0.01, by one-way ANOVA, n ═ 2 sections from 3 mice/group). In some embodiments, the treatment-dependent changes in EEA1 staining intensity are similar to the changes in Α β in CA1 (see, e.g., fig. 19A-19B, fig. 20A-20B, and fig. 24A-24B, p <0.05, by one-way ANOVA, n ═ 2 sections from 3 mice/group). These results indicate that in addition to the observed changes in CTF, 40-Hz stimulation altered EEA1 and Rab5, indicating differences in general endosomal processing.

Fig. 25A is a graph depicting a β peptide isoform a β after different types of stimulation of the CA1 region of the hippocampus of a subject, according to some embodiments _1-40 Horizontal bar graph of (a). In this experiment, one hour optogenetic stimulation 502 of FS-PV + at about 40Hz reduced A β in hippocampal CA1 _1-40 And (4) horizontal. Excitatory pyramidal stimulation 506 at 8Hz and excitatory pyramidal stimulation 508 at 40Hz did not significantly affect A β _1-40 And (4) horizontal. Random 40-Hz stimulation 504 and specifically random excitatory pyramidal stimulation 510 significantly increased A β _1-40 Levels (n-4-9 animals/group).

FIG. 25B is a block diagram depicting a method according to some embodimentsBar graph of the reduction of the a β peptide isoform a β 1-42 after stimulation of specific cell types in the CA1 region of hippocampus of a subject using gamma oscillations. In this experiment, one hour optogenetic stimulation 516 of FS-PV + at about 40Hz reduced A β in hippocampal CA1 _1-42 Levels (n-2-4 animals/group). Stimulation at 8Hz 520, excitatory pyramidal stimulation at 40Hz 522, and excitatory pyramidal stimulation at 8Hz 524 increase A β _1-42 And (4) horizontal. Random 40-Hz stimulation 518 and specifically random excitatory pyramidal stimulation 526 significantly increased A β _1-42 Horizontal).

Fig. 25C is a series of images showing an increase in the level of full-length APP 528, 534 (normalized to actin 532) and a decrease in the level of CTF (e.g., β -CTF)530, 536 (normalized to actin 532) after stimulation of a particular cell type in the CA1 region of the hippocampus of a subject using gamma oscillation, according to some embodiments. FS-PV + stimulation at 40-Hz decreased APP β -CTF levels and increased full-length APP levels compared to randomized 40-Hz control conditions (n-4-6 animals/group). Since β -CTF is an APP derivative produced during amyloidogenic cleavage of APP by BACE1, higher levels of β -CTF represent increased A β production.

Fig. 26A-26B are immunofluorescence images showing endosome levels (based on EEA1 levels) after different types of stimulation of the CA1 region of the hippocampus of a subject, according to some embodiments. Specifically, a comparison of fig. 26B to fig. 26A shows that induction of gamma oscillations by FS-PV +40-Hz stimulation reduced levels of EEA1 (a marker of endosomal levels) as measured by immunofluorescence compared to random FS-PV + stimulation 900 (n-3 mice/group, p-0.007). Reduced levels of endosomes in the cell are indicative of reduced interaction between APP and β -secretase, which results in reduced APP cleavage and a β production. Thus, the study showed that gamma oscillation reduced AP production in AD mouse models, as increased endosome levels indicated increased APP treatment and thus increased a β production.

Fig. 27 is a bar graph depicting mean intensity values (normalized to FAD) for the immunofluorescence images of fig. 26A-26B after different types of stimulation of the CA1 region of the hippocampus of the subject, according to some embodiments.

Gamma stimulation induces morphological transformation of microglia.

In some embodiments, to further explore the cellular and molecular roles of 40-Hz stimulation in an unbiased manner, whole genome RNA-seq of hippocampal CA1 was performed after one hour 40-Hz FS-PV-interneuron stimulation or no stimulation (EYFP) of 5XFAD/PV-Cre double transgenic mice. In the RNA-seq experiment, an average of 26,518,345 sequencing reads was obtained from three stimulated mice and three non-stimulated mice. Data QC analysis revealed an average of 183 for the exon/intron ratio, an average of 272 for the exon/intergene ratio, and an average of 3.6% for the percentage of ribosomal RNA reads. The analysis identified 523 Differentially Expressed Genes (DEG), of which 130 were up-regulated and 393 were down-regulated in response to 40-Hz stimulation.

FIG. 28 is a heat map presenting differentially expressed genes determined by the whole transcriptome RNA-seq of the mouse hippocampal CA1 region with and without 40-Hz stimulation. Normalized z-score values were calculated for each differentially expressed gene (row). Color represents relatively low and high levels of gene expression. Table 2 (below) presents 130 genes upregulated by 40-Hz FS-PV-interneuron stimulation (p <0.05, obtained from the Trapnell laboratory at washington university, seattle, washington, for assembly of transcripts, estimation of their abundance, and testing for differential expression and regulation in RNA-seq samples) using Cufflinks 2.2 software).

TABLE 2

Table 3 (below) presents 393 genes downregulated by 40-Hz FS-PV-interneuron stimulation (p <0.05, by Cufflinks 2.2 software (available from Trapnell laboratories, washington university, seattle, washington)).

TABLE 3

In some embodiments, an up-regulated gene generally has a higher expression value than a down-regulated gene. Figure 29 is a box plot showing FPKM values for up-and down-regulated genes in EYFP and 40-Hz conditions according to some embodiments. The box shows the median (black line in box) and quartile (top and bottom of box), the whiskers represent the minimum and maximum values, and the circles represent outliers. The up-regulated gene can be highly enriched in microglia. Specifically, about 35% of all up-regulated genes have their highest expression in microglia (of which about 19% are in neurons, about 17% in endothelial cells, about 14% in astrocytes, about 9% in myelinated oligodendrocytes, about 5% in oligodendrocyte precursor cells, and about 1% in newly formed oligodendrocytes).

Figure 30 is a pie chart showing cell type-specific expression patterns of up-regulated genes identified after 40-Hz stimulation according to some embodiments. Gene FPKM values were calculated from publicly available RNA-seq data from different brain cell types, including astrocytes, endothelial cells, microglia, Myelinated Oligodendrocytes (MO), neurons, newly formed oligodendrocytes (NFo), and Oligodendrocyte Precursor Cells (OPC). Thus, RNA-seq analysis strongly suggests that one hour 40-Hz stimulation of FS-PV-interneurons leads to a change in the cellular state of microglia, which is important in view of the increasing evidence that these cells play a role in AD pathology.

In some embodiments, to further explore the potential role of 40-Hz stimulation on microglia, a series of publicly available RNA-seq datasets from microglia, peripheral macrophages, and neurons under different chemical and genetic perturbations were compared to a list of genes from the characterization described in some embodiments herein using a gene set enrichment assay. Table 4 (below) shows the GSEA-based statistical significance of the correlation between genes up-and down-regulated by 40-Hz stimulation and neuron, microglia and macrophage specific RNA-seq data publicly available under different chemical and gene perturbations.

TABLE 4

Interestingly, the transcriptome changes after 40-Hz stimulation were more similar to those due to increased neural activity (via NMDA and bicuculline) and less similar to those due to silent activity (via tetrodotoxin). These findings also support the following findings: 40-Hz stimulation of FS-PV-interneurons did not reduce neuronal activity. Furthermore, immediate early genes Nr4a1, Arc and Npas4, which are known to be upregulated by neuronal activity, were elevated after one hour of 40-Hz stimulation, as shown by both RNA-seq and RT-qPCR. Fig. 31 is a bar graph showing RT-qPCR validation of specific gene targets in RNA-seq datasets, according to some embodiments. The bars show the relative RNA levels (fold change) from EYFP 3102 and 40-Hz stimulation 3104 conditions (one asterisk indicates p <0.05, two asterisks indicate p <0.01, and three asterisks indicate p <0.001, performed by Student's t-test, n-3 mice/group). Top down-regulated genes are Grin4 and Camk2d (see, e.g., fig. 31, p <0.05, n-3 mice/group).

In addition, transcriptome results indicate a more phagocytic state of microglia. In some embodiments, the up-regulated gene is positively correlated with genomic changes induced by Macrophage Colony Stimulating Factor (MCSF) and Granulocyte Macrophage Colony Stimulating Factor (GMCSF), both known to promote microglial a β uptake. Fig. 32A and 32B are graphs showing the power spectral density of the local field potential recorded above the brain during 40Hz light blinking according to some embodiments. Fig. 32A and 32B show that there was no increase in power at 40Hz, so the effect was not due to the photoelectric effect or electrical noise on the recording device (n ═ 4, 2, 1, 17, 42, 36, 55, 53 40-Hz blinking periods, 4 recording sessions from three 5XFAD animals undergoing visual cortex recordings and 5 recording sessions from two 5XFAD mice and three WT mice undergoing hippocampal recordings). The mean (solid line) and standard deviation (shaded area) across the recordings are shown on the left panel (fig. 32A) and the mean (solid line) and standard deviation (shaded area) for each animal are shown on the right panel (fig. 32B). Records 3202 with less than 3 flicker periods cause more power spectral density of noise than records 3204 with more data, but both do not show evidence of peaks at 40 Hz. In some embodiments, RT-qPCR is performed to verify up-regulated genes involved in known microglia function. Genes associated with microglial engulfment (including Cd68, B2m, Bst2, Icam1, and Lyz2) were confirmed to be upregulated in the hippocampal CA1 region following 40-Hz stimulation.

Fig. 33 is a bar graph depicting RT-qPCR validation of specific gene targets in RNA-seq datasets, according to some embodiments. Figure 33 shows relative RNA levels (fold change) in EYFP 3302 and 40-Hz stimulation 3304 conditions (one asterisk indicates p <0.05 and two asterisks indicate p <0.01, by Student's t-test, n ═ 6 mice/group). Other notable up-regulated genes include the microglia-rich transcriptional regulator Irf7, the cell adhesion and migration regulator Spp1, and the microglia proliferation markers Csf1r and Csf2ra (see, e.g., fig. 33, p <0.05 and p <0.01, by Student's t-assay, n ═ 6 mice/group). RT-qPCR also showed that the expression levels of pro-inflammatory genes Il6, Il1b (Il1- β), Itgam (CD11-b) and anti-inflammatory gene Igf1 were unchanged (see, e.g., fig. 33, p >0.05, by Student's t-test, n ═ 6 mice/group). Thus, the transcriptome results described herein indicate that 40Hz neuronal stimulation induces microglia into a state that promotes uptake.

Morphological features of microglial activation were examined in view of the 40-Hz stimulation to upregulate both phagocytosis-related genes and migration/cell adhesion-related genes. In some embodiments, antibodies recognizing the microglia marker Iba1 were used to label microglia from one hour of 40Hz, randomized or non-stimulated (EYFP mice) post 5XFAD/PV-Cre mice in hippocampal CA1 sections. FIG. 34 is a series of immunofluorescence images demonstrating immunohistochemistry in the hippocampal CA1 region of 5XFAD/PV-Cre mice using anti-Iba 13402 (019-19741) and anti-A β 3404(12F4) antibodies in EYFP, 40-Hz and random stimulation conditions. Images were taken using a 40x objective lens, scale bar 50 μm). Arrows indicate + Iba1/+ a β signals in the cell body.

Fig. 35A is a bar graph depicting the number of microglia in EYFP and 40-Hz conditions according to some embodiments (n-2 sections from 4 mice/group). Figure 35B is a bar graph depicting the diameter of microglia cell bodies normalized to EYFP in EYFP, 40-Hz, and random stimulation conditions according to some embodiments (n ═ 2 sections from 4 mice/group). Fig. 35C is a bar graph depicting the average length of microglia primary processes or processes normalized to EYFP in EYFP, 40-Hz and random stimulation conditions EYFP, 40Hz, and random, according to some embodiments. Fig. 35D is a bar graph depicting the percentage of Iba 1-positive (microglia) cell bodies that were also Α β -positive in EYFP and 40-Hz stimulation conditions according to some embodiments (n ═ 2 sections from 4 mice/group). The symbol "n.s." 3502 indicates insignificant, two asterisks 3504 indicate p <0.01, three asterisks 3506 indicate p <0.001, and four asterisks 3508 indicate p <0.0001, by one-way ANOVA.

First, the number of Iba1+ microglia in 6 animals/conditions was counted and compared to unstimulated EYFP conditions (average of 8 microglia/ROIs) (see, e.g., fig. 34 and 35A, p <0.01, by one-way ANOVA, n ═ 2 sections from 4 mice/group) and to randomized conditions (average of 10 microglia/ROIs) (see, e.g., fig. 34 and 35A, p <0.05, by one-way ANOVA, n ═ 2 sections from 4 mice/group) and almost twice as many microglia in the 40Hz group were observed (15 microglia/212.55 μm x 212.55 μm region of interest (ROI)). Previous studies have shown that two main features of phagocytic microglia are increased cell body size and decreased process length, thus examining how these features are affected by 40-Hz stimulation. In some embodiments, the diameter of each clearly labeled Iba1+ cell body in the field of view is measured. Microglial body diameter was found to increase by 135.3% following 40-Hz stimulation compared to no stimulation and 138.7% compared to randomized conditions (see, e.g., figure 34 and figure 35B, p <0.0001, by one-way ANOVA, n ═ 2 sections from 4 mice/group). The length of primary processes of microglia in each condition was measured and a 54.0% reduction in primary microglia process length compared to EYFP control and a 38.5% reduction compared to random stimulation in 40-Hz stimulation conditions was observed (see, e.g., figure 34 and figure 35C, p <0.0001, by one-way ANOVA, n ═ 2 sections from 4 mice/group). These findings were not affected by Iba1 levels, as no difference in Iba1 expression between conditions was observed in the gene expression analysis described herein (see, e.g., tables 2 and 3). Thus, the increase in cell body size and decrease in process length observed after 40-Hz stimulation are morphological changes consistent with the migration of these microglia towards a phagocytic state. After co-immunostaining with the a β antibody (12F4, which does not cross-react with APP), potential co-localization of a β within microglia was evaluated as a means to assess microglia a β uptake. In the CA1 neuro-fiber network with Iba1+ cells predominantly localized, the ratio of the number of microglia with a β/Iba1 co-localization (ImageJ, Fuji co-localization insert) to the total number of microglia in the cell body increased by 54.9% compared to EYFP control and 50.3% compared to random conditions after 40-Hz stimulation (see, e.g., fig. 34 and 35D, p <0.01, by one-way ANOVA, n ═ 2 sections from 4 mice/group). Iba1/a β signal overlap during microglia was excluded to avoid inclusion of potential random non-engulfed co-localization.

In some embodiments, to provide better resolution of the presence of a β signals within microglia, 3D renderings of microglia from this tissue and video from these renderings are created. Fig. 36 is a series of 3D renderings formed by merging the immunofluorescence images from fig. 34, 3602 rotated 0 degrees, 3604 rotated-25 degrees about the Y-axis, and 3606 rotated 30 degrees about the X-axis, according to some embodiments. Images were taken using a 40x objective (scale bar 50 μm). Taken together, gene expression and morphological analyses indicate that 40-Hz stimulation affects microglial activity by increasing recruitment of microglia to the stimulation site and enhancing their engulfment activity, resulting in increased association with a β. Importantly, in some embodiments, no evidence of neuronal loss was found by measuring the thickness of the CA1 cell layer using nuclear staining with Hoechst. The mean CA1 volume did not differ significantly between the EYFP and 40-Hz stimulation groups.

Figure 37A is a series of immunofluorescence images showing immunohistochemistry using Hoechst in the hippocampal CA1 region of 5XFAD/PV-Cre in EYFP and 40-Hz stimulation conditions according to some embodiments. Fig. 37B is a bar graph depicting estimated CA1 thickness of 5XFAD/PV-Cre in EYFP and 40-Hz stimulation conditions according to some embodiments (n ═ 4 mice/group, "n.s." indicates not significant, by Student's t-test).

Next, according to some embodiments, differential gene expression in 5XFAD mice infected with AAV-DIO-ChR2-EYFP and stimulated with 40-Hz FS-PV + stimulation (TREAT) or control stimulation (CTRL) was assessed by whole genome RNA-seq of hippocampal CA1 after one hour of stimulation. Fig. 38A is a heat map showing 523 Differentially Expressed Genes (DEG) determined by whole genome RNA-seq of hippocampal CA1 following TREAT or CTRL according to some embodiments. Each row in figure 38A represents DEG and the columns in figure 38A represent the transcriptome profiles of three individual control animals and three individual treated (40-Hz FS ═ PV + stimulated) animals.

Fig. 38B is a graph showing overlap between DEG upregulated in the TREAT condition in fig. 38A, according to some implementations. In fig. 38B, induction of gamma oscillations by FS-PV +40-Hz stimulation reduced Iba1 levels compared to random FS-PV + stimulation as measured by immunofluorescence (n-3 mice/group, p-0.006). Figure 38B shows that genes upregulated in TREAT conditions significantly and specifically overlap with microglia genes upregulated by anti-inflammatory microglia activation (i.e., MCSF genes). Genes are upregulated in microglia with a degree of upregulation greater than in astrocytes, endothelial cells, Myelinated Oligodendrocytes (MO), neurons, Newly Formed Oligodendrocytes (NFO), and Oligodendrocyte Precursor Cells (OPC). Table 5 (below) presents the microglia/macrophage pathway for up-regulation of genes.

TABLE 5

According to some embodiments, RT-qPCR is performed to validate specific gene targets from the RNA-seq dataset. Fig. 39 is a bar graph depicting RT-qPCR validation of specific gene targets in the RNA-seq dataset of fig. 38A, according to some embodiments. Specifically, FIG. 39 shows fold-change (normalized to GAPDH) of specific gene targets (including genes CSF1, CSF1R, ll-6, ll1- β, CD11-b, CYBA, Hmox1, H2-K1, Lgals3, and Icam1) in control and treatment conditions.

Fig. 40 is a diagram showing biological processes to which the upregulated genes of fig. 38A are associated, according to some embodiments. Importantly, the up-regulated genes in figure 40 are specifically associated with immune-related processes. Upregulation genes belong to immune-related biological processes including lymphocyte-mediated processes, adaptive immune processes and immunoglobulin-mediated processes. Fig. 41 is a diagram showing biological processes to which the down-regulated genes of fig. 38A are associated, according to some embodiments. Downregulating genes belong to biological processes including cell movement, cell-cell signaling, synaptic transmission, motor behavior, and neuronal processes, as shown in figure 41.

Fig. 42A is a series of immunofluorescence images showing levels of Iba1 following different types of stimulation of the CA1 area of the hippocampus of a subject, according to some embodiments. Fig. 42B is a bar graph depicting the mean intensity values for the immunofluorescence image of fig. 42A, according to some embodiments. Figure 42A shows a decrease in endosome levels by optogenetic enhancement of gamma rhythm. Induction of gamma oscillation by FS-PV +40-Hz stimulation reduced the level of EEA1 (marker of endosomes), as measured by immunofluorescence (n-3 mice/group, p-0.08). The results show that gamma oscillations reduce a β production in AD mouse models, as increased endosome levels indicate increased APP treatment and thus increased a β production.

Taken together, the results of the study show that the restoration or induction of gamma rhythm restores molecular lesions in a mouse model of AD. Cell type specific and temporally precise reintroduction of gamma oscillations by optogenetics reduces isoform a β _1-40 And Abeta _1-42 And enhance its clearance, the peptides aggregate to trigger many degenerative cascades that are involved in AD neuropathy. In addition, this treatment induces anti-inflammatory microglial signaling pathways that counteract immune mechanisms associated with neurodegeneration.

According to some embodiments, cell-type specific and temporally controlled gamma oscillations may be induced in the hippocampus, visual cortex, tubal cortex, and/or auditory cortex without optogenetics.

Visual stimuli at gamma frequencies non-invasively drive gamma oscillations in the visual cortex.

The significant reduction in a β levels by optogenetic stimulation at 40Hz led to the exploration of other ways to induce 40-Hz oscillations in the brain in order to ensure that the effects are not in some way specific for optogenetic manipulation or invasive procedures. To examine whether light blinking can be used as a non-invasive way of inducing 40-Hz oscillations in the visual cortex, in some embodiments, animals are exposed to periods of 40Hz or random blinking and continuous light interleaved with periods of darkness.

Figure 43A is a schematic showing a mouse exposed to a light scintillation stimulus, according to some embodiments. To determine whether this light flash altered a β, animals were exposed to 40-Hz light flashes for one hour, consistent with the duration of the optogenetic stimulus that reduced a β as described herein. The light flashes cover the entire field of view of the animal. As controls for molecular and cellular assays, march-old 5XFAD mice were maintained in constant darkness for three days or treated with constant light or 20-Hz blinking light or 80-Hz blinking light for one hour (see, e.g., fig. 43A).

Fig. 43B includes plots of local field potential traces and power spectral density in the visual cortex before and during 40-Hz light flicker according to some embodiments. Mean (solid line) and standard deviation (shaded area) of power spectral density in visual cortex during 40-Hz light flicker 4302, random light flicker 4304 or dark 4306 are indicated (n-4 from 5FXFAD mice for 5 recording sessions only). Fig. 43C-43F are graphs depicting power spectral densities of local field potentials in the visual cortex during 40-Hz light flicker, random light flicker, constant darkness, and constant light, respectively, for each recording session of each mouse (n ═ 5 recordings from four 5XFAD mice using 47, 51, 61, 49, 16 40-Hz flickers, 47, 50, 64, 50, 16 random flickers, 279, 302, 382, 294, 93 darkness, and 47, 50, 64, 49, 15 light time periods), according to some embodiments. In the visual cortex, it was found that light blinking at 40Hz increased the power in the LFP at 40Hz (see, e.g., fig. 43B and 43C), while randomly spaced light blinking and darkness did not increase the power (see, e.g., fig. 43B, 43D, and 43E).

Fig. 44A is a series of histograms depicting the fraction of spikes in the visual cortex as a function of time for random light flashes for four cycles and an equivalent time period of 40-Hz light flashes, according to some embodiments. Fig. 44A shows a histogram of the fraction of spikes in visual cortex as a function of time for 4 cycles 4402 of 40-Hz light flashes or an equivalent time period of random light flashes 4404 (n-four 5XFAD mice from five recording sessions, bars indicate mean and error bars indicate SEM across animals). The upper bar indicates when the light turns on 4406 or turns off 4408. In some embodiments, the spikes increase and decrease with light blinking on and off, causing a spike phase that locks to the 40-Hz frequency during 40-Hz stimulation (histogram 4402 in fig. 44A), but no significant frequency occurs during random stimulation (histogram 4404 in fig. 44A).

Fig. 44B is a series of electrical traces of local field potentials recorded above the brain during light blinking according to some embodiments. In some embodiments, the increase in 40Hz power during 40-Hz blinking was not found when recorded from saline directly above the brain, showing that this effect is not due to the photoelectric effect or electrical noise (see, e.g., fig. 32 and 44B). As in the case of optogenetic stimulation, random blinking provides a control for the overall change in activity due to light blinking.

Fig. 45A is a bar graph showing the difference in firing rate between 40-Hz light flashes and random light flashes (n-226 stimulation periods from five recording sessions in four 5XFAD mice), according to some embodiments. Fig. 45B is a graph showing multiple unit firing rates in the visual cortex during 40-Hz light flashes, random light flashes, darkness, and light periods, according to some embodiments. Fig. 45B shows the multi-unit firing rate in the visual cortex. The box whisker plots the median (white line in the box) and quartile (top and bottom of the box). The firing rate between 40-Hz flash and random flash conditions was not significantly different in all animals, showing that random stimulation conditions served as a control for spiking activity (p >0.06 for rank and test for each of 5 recording sessions from four 5XFAD mice, median and quartile shown in the figure, n-47, 51, 64, 49, 16 40-Hz flash periods and 47, 50, 64, 50, 16 random flash periods/recordings). There was no significant difference in firing rate between 40-Hz blinking and light conditions, indicating that 40-Hz light blinking typically did not result in neuronal hyperexcitability (for the rank and test of each of 5 recording sessions from four 5XFAD mice, p >0.2 for 4 recording sessions, p > 0.01 for 1 recording session, this was not significant when correcting for performing multiple comparisons, median and quartile are shown in the figure, n ═ 47, 51, 64, 49, 16 40Hz time periods and 47, 50, 64, 49, 16 light time periods/recordings). In one session, there is more activity in 40-Hz stimulation than in dark conditions. The difference in multi-unit firing rates between 40Hz and the random blinking time period tends to be near zero (see, e.g., 45A); and no significant differences were found in comparing these time periods within the animals (see, e.g., figure 45B, p >0.06, median and quartile shown in the figure for rank and test for each of 5 recording sessions from four 5XFAD mice, n ═ 47, 51, 64, 49, 16 γ scintillation time periods and 47, 50, 64, 50, 16 random scintillation time periods/recordings).

Visual stimuli at gamma frequencies reduce a β levels in the visual cortex.

In view of the efficacy of the optogenetic approach, a translational, non-invasive amyloid-reducing treatment was devised. Fig. 46A is a schematic diagram showing an experimental example according to some embodiments. As shown in fig. 46A, a first subset of AD model mice are placed in a first chamber 4600 with 40-Hz flashes, and a second subset of AD model mice are placed in a second chamber 4602 that remains dark. Animals in first chamber 4600 were exposed to a 40-Hz flash of light for about one hour.

Fig. 46B and 46C are diagrams that further show a β peptide isoform a β, respectively, after the experimental paradigm of fig. 46A according to some embodiments _1-40 And Abeta _1-42 A graph of changes in baseline levels of (a). FIG. 46B shows that 40-Hz light exposure of 5XFAD mice significantly reduced A β in the visual cortex V1 _1-40 And Abeta _1-42 Level of。Aβ _1-40 And Abeta _1-42 Levels are presented as pg/mL (n ═ 6 animals/group).

Whereas 40-Hz light flicker drives 40-Hz oscillations in the primary visual cortex and optogenetic induction of 40-Hz oscillations reduces hippocampal A β levels, the goal was to determine whether 40-Hz light flicker can reduce A β levels in the visual cortex. For these experiments, in some embodiments, 5XFAD mice that are three months old before symptoms are used. Mice were placed in a dark box and exposed to 40-Hz light flashes, constant light on (light), or constant light off (dark) for one hour.

FIGS. 47A and 47B are graphs depicting A β in the 5XFAD visual cortex in dark, light, 40-Hz glint, 20-Hz glint, 80-Hz glint, 40-Hz glint using Picrotoxin (PTX), and random glint conditions, respectively, according to some embodiments _1-40 And Abeta _1-42 Bar graph of changes in baseline levels of (n-12 mice/group for dark; n-6 mice/group for light, 40-Hz flash, 20-Hz flash, 80-Hz flash, and PTX; n-4 mice/group for random flash; "n.s." indicates non-significant, one asterisk indicates p<0.05, and two asterisks indicate p<0.01, by one-way ANOVA). Fig. 47A and 47B show the average values and SEM. The circles in the bar graph superimposed on the bars indicate the individual data points in each group. After one hour after light exposure, a β in the visual cortex was observed compared to dark conditions _1-40 The level was reduced by 57.96% and Abeta _1-42 The reduction in levels is 57.97% (as measured by a β ELISA, see, e.g., fig. 47A and 47B, p<0.05, by one-way ANOVA, n ═ 6 mice/group). Amyloid levels were reduced by 62.47% (a β) after one hour of 40-Hz scintillation compared to light control _1-40 ) And 68.55% (A.beta.) _1-42 ) (as measured by A.beta.ELISA, see, e.g., FIG. 47, p<0.05, by one-way ANOVA, n ═ 6 mice/group). Furthermore, the effect was specific for 40-Hz blinking, as neither 20-Hz, 80-Hz, or random blinking significantly reduced Α β levels compared to dark and light controls (see, e.g., fig. 47, "n.s." indicates insignificant, n-6 mice/group)。

In some embodiments, to test for regional specificity, Α β levels in the somatosensory Barrel Cortex (BC) were examined and no significant difference was found. FIG. 48A is a graph depicting the relative A β of 5XFAD tubiform cortex under dark and 40-Hz scintillation conditions according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graphs (n ═ 3 mice/group; "n.s." indicates non-significance, by Student's t-test). When 5XFAD mice were pretreated with low dose GABA-a antagonist (picrotoxin, 0.18mg/kg, which does not induce epileptic activity), the effect of 40-Hz blinking on Α β levels was completely abolished, indicating that γ -aminobutyric acid signaling (most likely from FS-PV-interneuron) is essential for this effect (see, e.g., figure 47, "n.s." indicates no significance, n ═ 6 mice/group).

To demonstrate that the effect is not specific for 5XFAD mice, this result was repeated in different AD model APP/PS1 mice (well-validated model with two familial AD mutations (APP sweden and PSEN1 deltaE 9). FIG. 48B is a graph depicting A β in APP/PS1 visual cortex under dark and 40-Hz glint conditions according to some embodiments _1-40 And Abeta _1-42 Bar graph of changes in baseline levels of (n 5 mice/group for dark condition and n 4 mice/group for 40-Hz blinking condition; "n.s." indicates non-significant and one asterisk indicates p<0.05, by Student's t-test).

FIG. 48C is a graph depicting A β in WT visual cortex under dark and 40-Hz glint conditions, according to some embodiments _1-40 And Abeta _1-42 Bar graph of changes in baseline levels of (n 11 mice/group for dark condition and n 9 mice/group for 40-Hz blinking condition; one asterisk indicates p<0.05, by Student's t-test). In some embodiments, A β is found in APP/PS1 mice after 40-Hz scintillant treatment _1-40 The significant reduction of 20.80 percent and A beta _1-42 A trend of 37.68% reduction, although the latter was not significantly different from dark conditions (see, e.g., fig. 48B, a β _1-40 p<0.05，Aβ _1-42 p<0.09-not significantPerformed by Student's t-test, n-5 mice/group for dark and 4 mice/group for 40-Hz scintillation). Furthermore, in aged WT mice, endogenous mouse A β was found after one hour of 40-Hz blinking _1-40 58.2% reduction (see, e.g., FIG. 48C, p<0.05, by Student's t-test, n-11 dark mice and n-9 40-Hz scintillation mice). In these animals, A.beta. _1-42 Below detectable levels for both scintillation and control groups. Endogenous mouse a β in WT animals _1-40 Reduction of (d) reveals that these results may not be limited to Tg APP expression or mutant APP; instead they may extend to a β produced from APP, expression being driven by its endogenous promoter. Fig. 48A-48C show mean values and SEM.

Next, in some embodiments, a survey was conducted to determine whether 40-Hz blinking altered microglial activity in the visual cortex in the same manner as 40-Hz optogenetic FS-PV-interneural stimulation altered hippocampal CA1 microglia. FIG. 49 is a series of immunofluorescence images showing immunohistochemistry using anti-Iba 1 (019-and 19741) and anti-A β 4904(12F4) antibodies in a 5XFAD visual cortex under dark and 40-Hz scintillant conditions according to some embodiments. Images were taken using a 40x objective (scale bar 50 μm). Right panel: amplifying by 120X; arrows indicate + Iba1/+ a β signals in the cell body.

Figure 50A is a bar graph depicting the number of microglia cells in dark and 40-Hz flash conditions (n ═ 2 sections from 4 mice/group; "n.s." indicates non-significant, by Student's t-test) according to some embodiments. Figure 50B is a bar graph depicting the diameter of microglia cell bodies normalized to controls in dark and 40-Hz blinking conditions according to some embodiments (n-2 sections from 4 mice/group; two asterisks indicate p <0.01, by Student's t-test). Figure 50C is a bar graph depicting the average length of microglia primary processes normalized to control in dark and 40-Hz scintillation conditions according to some embodiments (n ═ 2 sections from 4 mice/group; four asterisks indicate p <0.0001, by Student's t-test). Figure 50D is a bar graph depicting the percentage of Iba 1-positive (microglia) cell bodies that are also Α β -positive under dark and 40-Hz blinking conditions according to some embodiments (n ═ 2 sections from 4 mice/group; two asterisks indicate p <0.01, by Student's t-test). Fig. 50A-50D show mean values and SEM.

In some embodiments, Iba1 is used to label microglia in a visual cortex section of a 5XFAD mouse after one hour of 40-Hz flash or dark conditions (see, e.g., fig. 49). Although microglial numbers were not different between dark and 40-Hz blinking conditions (see, e.g., fig. 49 and 50A, "n.s." indicates insignificant, n ═ 2 sections from 4 mice/group), microglial body diameters increased by 65.8% in the visual cortex after 40-Hz blinking compared to dark controls (see, e.g., fig. 49 and 50B, p <0.01, by Student's t-test, n ═ 2 sections from 4 mice/group). The length of microglia primary process decreased by 37.7% in 40-Hz blinking conditions compared to dark controls (see, e.g., figure 49 and figure 50C, p <0.0001, by Student's t-test, n ═ 2 sections from 4 mice/group). In some embodiments, the number of microglia carrying a β is examined because the microglia in the visual cortex have a morphology indicating enhanced swallow activity. For this experiment, visual cortical sections were co-labeled with Iba1 and a β (12F4) antibodies. Co-localization of a β/Iba1 in cell bodies increased by 33.5% in 40-Hz blinking conditions, indicating that 40-Hz blinking caused more Α β -bearing microglia cells than dark controls (see, e.g., figure 49 and figure 50D, p <0.01, by Student's t-test, n ═ 2 sections from 4 mice/group)

In some embodiments, to provide better resolution of morphological changes in microglia, classification is used to create 3D renderings of microglia from 100 μm slices of the visual cortex and video is created from these renderings. Figure 51 is a series of 3D renderings (from immunofluorescence images) of Iba + microglia under dark and 40-Hz scintillation conditions from category-treated 100 μm tissue sections, 5102 rotated 0 °, 5104 rotated 45 ° about the X-axis, and 5106 rotated 45 ° about the Y-axis. Images were taken using a 63x objective (scale bar 15 μm). Finally, to demonstrate that microglia indeed engulf a β in 5XFAD mice, microglia from 5XFAD and WT animals were purified using Fluorescence Activated Cell Sorting (FACS) and analyzed for a β levels by ELISA.

Fig. 52A is a flow diagram showing a method for isolating microglia from visual cortex using Fluorescence Activated Cell Sorting (FACS), according to some embodiments. The visual cortex was dissected and single cells were then suspended and labeled with CD11b and CD45 antibodies. Subsequently, the cells were sorted by Fluorescence Activated Cell Sorting (FACS) and lysed. Analysis of A.beta.by ELISA _1-40 And (4) horizontal. Figure 52B is a graph depicting a β in microglia cells isolated from the visual cortex of march-old 5XFAD and WT control animals using the method of figure 52A, according to some embodiments _1-40 Horizontal bar graph (n-8 mice/group for 5XFAD and 4 mice/group for WT mice; one asterisk indicates p<0.05, by Student's t-test). The circles in the bar graph superimposed on the bars indicate the individual data points in each group.

Figure 53A is a series of immunofluorescence images demonstrating immunohistochemistry using SVP38 antibody to detect synaptic vesicle proteins in a march-old 5XFAD visual cortex under dark and 40-Hz scintillation conditions according to some embodiments. Images were taken using a 40x objective (scale bar 50 μm). Right panel: 100X darkness and 40-Hz flicker conditions. Fig. 53B is a bar graph depicting the relative SVP38 intensity levels of 5XFAD visual cortex after dark and 40Hz flash conditions (n 4 mice/group; "n.s." indicates not significant, by Student's t-test), according to some embodiments.

Microglial-specific levels of a β were found to be significantly higher in 5XFAD animals than WT controls, with 27.2pg/10 in 5XFAD mice ⁴ At the level of microglia and at 9.78pg/10 in WT control mice ⁴ At the level of microglia (see, e.g., FIG. 52A and FIG. 52B, p)<0.05, by Student's t-test, n-8 for 5XFAD and 4 for WT mice). In these animals, A.beta. _1-42 Below detectable levels for both scintillation and control groups. Overall, the microglial transformation induced in the visual cortex by 40-Hz stimulation appeared similar to that occurring in hippocampal CA 1. In addition, synaptic vesicle protein levels did not change between dark and 40-Hz blinking conditions, indicating that microglial activation did not significantly increase synaptic engulfment (see, e.g., fig. 53A and 53B, "n.s." indicates insignificant, n ═ 2 sections from 4 mice/group). Taken together, the data disclosed herein demonstrate that non-invasively induced 40-Hz oscillations by sensory stimulation can effectively reduce Α β abundance and promote microglia/Α β interactions in an AD mouse model. Furthermore, 40-Hz stimulation can reduce a β in two distinct brain circuits, suggesting that gamma oscillations decrease amyloid abundance and enhance the general mechanism of microglial phagocytosis in various brain regions.

In another experiment, A β was assessed after one hour exposure to darkness (no light), 20-Hz flash, 40-Hz flash, or 80-Hz flash _1-42 Horizontal, where 20Hz and 80 Hz are harmonics of 40 Hz. However, flash flicker at only 40Hz significantly reduced A β _1-42 And (4) horizontal. Figure 54A is a graph showing a β peptide isoform a β after stimulation of the visual cortex of a subject using gamma oscillation, according to some embodiments _1-42 Reduced bar graph of (2).

Another study was conducted to assess A β _1-42 Time to decrease the level. Mice were exposed to either no light or 40-Hz flash for one hour. Determination of A.beta.after one hour treatment _1-42 Level, and a β was determined again 24 hours after the treatment was completed _1-42 And (4) horizontal. Fig. 54B is a graph showing a β peptide isoform a β once more after stimulation of the visual cortex of a subject with gamma oscillation and twenty-four hours after stimulation, according to some embodiments _1-42 Horizontal bar graph of (2). Although A β levels were twenty-four hours after treatmentThe reduction remains, but is less than the reduction immediately after treatment.

Visual stimuli at gamma frequency did not affect Α β levels in the hippocampus.

In some embodiments, to determine whether visual stimulation by light glints can affect brain circuits involving AD, the effect of light glints on the hippocampus, one of the brain regions affected early in the AD process in humans, was examined. Fig. 55A includes plots of electrical traces and power spectral density of local field potentials in a hippocampus before and during 40-Hz photo-scintillation 5502 according to some embodiments. Mean (solid line) and standard deviation (shaded area) of power spectral density during dark 5504, 40-Hz light flashes 5506 and random light flashes 5508 in CA1 (n ═ two 5XFAD mice and three WT mice).

Fig. 55B is a series of histograms of spike scores in hippocampus as a function of time for 4 cycles 5510 or equivalent time periods of 40-Hz light scintillation, respectively 5512 (n ═ two 5XFAD mice and three WT mice, bars indicate mean and error bars indicate SEM across animals), according to some embodiments. The bar above indicates when the light is on (white) or off (black). For random stimulation, the spikes are aligned with the start of light on, with additional time periods of light occurring at random intervals indicated by grey. Using the same method to examine the effect of light flicker in CA1 as disclosed herein in the visual cortex, it was found that light flicker at 40Hz increased the power recorded at 40Hz in LFP (see, e.g., fig. 55A and fig. 55B, graph 5510), while randomly spaced light flicker (random flicker) and darkness did not increase the power (see, e.g., fig. 50D, fig. 43C, graph 4310). The spikes are also modulated by the 40-Hz blinking frequency during 40H stimulation, however, the modulation appears to be smaller in the visual cortex (see, e.g., fig. 55B, hippocampus, fig. 44A, visual cortex).

Figure 56A is a bar graph showing the difference in firing rate between 40-Hz light flashes and random light flashes (bottom n-168 stimulation periods from 5 recording sessions in two 5XFAD mice and three WT mice), according to some embodiments. Fig. 56B is a graph demonstrating multiple unit firing rates in CA1 during a 40-Hz light flicker 5604, random light flicker 5605, darkness 5602, or light 5608 time period, according to some embodiments. The box whisker plots the median (white line in the box) and quartile (top and bottom of the box). The firing rate between 40-Hz flash and random flash conditions was not significantly different in all animals, showing that random stimulation conditions served as controls for spiking activity (p >0.2 for rank sum tests of each of 5 recordings from two 5XFAD animals and three WT animals, median and quartile shown in the figure, n-22, 54, 42, 71, 55 40-Hz flash periods and 12, 34, 32, 54, 36 random flash periods/recordings). There was no significant difference in firing rate between 40-Hz flash and light conditions, indicating that 40-Hz light flash generally did not result in neuronal hyperexcitability (p >0.3 for the rank sum test from each of 5 recordings from two 5XFAD animals and three WT animals, with median and quartile numbers shown in the figure, n ═ 22, 54, 42, 71, 55 40Hz time periods and 12, 34, 33, 54, 35 light time periods/recordings).

As in the visual cortex, the difference in multi-unit firing rates between 40Hz and random flash time periods tends to be near zero (see, e.g., fig. 56A), and no significant differences were found when these time periods were compared within animals (see, e.g., fig. 56B, p >0.06 for rank-sum tests for each of 5 recording sessions from four 5XFAD mice, median and quartile shown in the figure, n-22, 54, 42, 71, 55 40-Hz flash time periods and 12, 34, 32, 54, 36 random flash time periods/recordings).

In some embodiments, the effect of visual light flicker on the level of a β in the hippocampus was examined using the same method used in the visual cortex. FIG. 57A is a graph depicting the relative A β in the 5XFAD visual cortex _1-40 Horizontal bar graph, and figure 57B is a graph depicting relative Α β in 5XFAD visual cortex according to some embodiments _1-42 Horizontal bar graphs (n-4 mice/group; "n.s." indicates non-significant). In CA1, flickering at 40-Hz, compared to that observed in the visual cortexOr one hour after random stimulation, no A.beta.was found _1-40 And Abeta _1-42 Significant difference between levels. The a β levels after 40-Hz blinking or random blinking are not significantly different from dark conditions: 40Hz and Abeta after random flicker _1-40 Levels were 108.4% and 96.82% of dark conditions, respectively, and 40-Hz and A β after random flicker _1-42 Levels were 118.8% and 92.15% of dark conditions, respectively (see, e.g., fig. 57A and 57B, "n.s." indicates non-significant, n-4 mice/group). Thus, a 40-Hz light flash of one hour did not significantly reduce the level of A β in the hippocampus.

Chronic visual stimulation at gamma frequencies reduces plaque burden in the visual cortex.

Affected amyloid abundance in pre-plaque 5XFAD mice when 40-Hz oscillating light is driven genetically or by visual stimulation via light scintillation has been examined and disclosed herein. Next, the goal was to determine if this treatment was effective in animals that had shown plaque burden. To this end, in some embodiments, june-large 5XFAD mice are used because they develop extensive amyloid plaque lesions in many brain regions, including the visual cortex. Tests were conducted to ascertain what advanced a β -related lesions would occur following non-invasive gamma stimulation. In some embodiments, to investigate the duration of a β reduction in response to one hour of 40-Hz blinking, a β levels were measured in the visual cortex at 4 hours, 12 hours, and 24 hours after one hour of 40-Hz blinking or dark conditions.

FIGS. 58A and 58B are graphs depicting relative Abeta of a 1 hour, 4 hours, 12 hours, and 24 hours 5XFAD visual cortex after one hour of darkness or 40-Hz flicker treatment, respectively, according to some embodiments _1-40 And Abeta _1-42 Horizontal bar graph (n 4 mice/group for 4 and 12 hours, n 6 for 1 and 24 hours, n 12 for darkness; "n.s." indicates non-significant, one asterisk indicates p<0.05, and two asterisks indicate p<0.01, by one-way ANOVA). The results show that a β is after 4 hours compared to the dark control _1-40 The level was reduced by 63.4% and Abeta _1-42 The level is reduced by 63.2% (see, e.g., FIG. 58, p)<0.01, n-4 mice/group). By 12 hours, Abeta _1-40 The level is reduced by 50.9%, and Abeta _1-42 Levels are not significantly different from dark controls (see, e.g., fig. 58, "n.s." indicates non-significant and p<0.01, n-4 mice/group). Finally, 24 hours after one hour of 40-Hz scintillation treatment, soluble A β in 40-Hz scintillation compared to dark control conditions _1-40 And Abeta _1-42 The levels were not significantly different (see, e.g., figure 58, "n.s." indicates non-significant, n 6 mice/group for 24 hours and 4 mice/group for dark). These results indicate that the effect of the 40-Hz scintillation process is transient.

Thus, in some embodiments, to destroy advanced plaque lesions, mice are treated with 40-Hz scintillation for one hour per day for seven days, or for controls, with dark conditions. Fig. 59A is a schematic diagram depicting a june-sized mouse exposed to one hour of scintillation per day for seven days, according to some embodiments. FIG. 59B is a graph showing relative A β in the visual cortex of a sixty-month-old 5XFAD mouse after seven days of one hour/day under dark or 40-Hz blinking conditions, according to some embodiments _1-42 Horizontal bar graph (n-13 mice/group, two asterisks indicate p<0.01 and three asterisks indicate p<0.001, Student's t-test). FIG. 59C is a graph showing relative Abeta in the visual cortex of a sixty-month-old 5XFAD mouse after seven days of one hour/day under dark or 40-Hz blinking conditions, according to some embodiments _1-40 Horizontal bar graph (n-13 mice/group, one asterisk indicates p<0.01 and two asterisks indicate p<0.01, by Student's t-test). Fig. 59B and 59C show the mean values and SEM. The circles in the bar graph superimposed on the bars indicate the individual data points in each group.

At the end of the seven day period, the visual cortex was analyzed by ELISA and immunostaining. In some embodiments, tissues were lysed in Phosphate Buffered Saline (PBS) to extract PBS soluble a β fraction and it was found that in june-sized 5XFAD mice, one hour of 40-Hz scintillation for seven days caused soluble a β to flash _1-40 And Abeta _1-42 Levels were reduced by 60.5% and 51.7%, respectively, as measured by ELISA (see, e.g., fig. 59B and 59C, p<0.05 and p<0.01, by Student's t-test, n-13 mice/group). Further treatment of the tissue with guanidino hydrochloric acid (HCl) for extraction of insoluble Abeta _1-40 And Abeta _1-42 A fraction which constitutes aggregated amyloid plaques. Insoluble Abeta _1-40 And Abeta _1-42 The levels were reduced by 43.7% and 57.9%, respectively, indicating that 40-Hz scintillation destroyed insoluble Α β aggregates that had formed in june-old mice (see, e.g., fig. 59B and 59C, p)<0.01 and p<0.001, by Student's t-test, n-13 mice/group).

In some embodiments, to determine how plaque burden is specifically affected, immunohistochemical characterization (cell signaling techniques; D54D2) was performed using the a β antibody. Fig. 60A is a series of immunofluorescence images (scale bar 50 μ ι η) showing immunohistochemistry using a β (D5452) antibody in the visual cortex of june-sized 5XFAD mice after seven days of one hour/day under dark (top) or 40-Hz blinking (bottom) conditions according to some embodiments. Excluding the presence of intracellular A β signals. Figure 60B is a bar graph depicting the number of Α β -positive plaque deposits in the visual cortex of june-large 5XFAD mice after seven days of one hour/day under dark or 40-Hz blinking conditions (n-8 mice/group, three asterisks indicate p <0.001, by Student's t-test) according to some embodiments. Figure 60C is a bar graph depicting the area of Α β -positive plaques in the visual cortex of june-large 5XFAD mice after seven days of one hour/day under dark or 40-Hz blinking conditions, according to some embodiments (n ═ 8 mice/group; two asterisks indicate p <0.01, by Mann Whitney test). Fig. 60B and 60C show the mean values and SEM.

Plaque abundance was quantified by counting the number of Α β + deposits greater than or equal to about 10 μm in diameter. 40-Hz scintillation reduced the number of plaques to 11.0 compared to 33.5 in the dark control (see, e.g., figure 60A and figure 60B, p <0.01, by Student's t-test, n-8 mice/group). Furthermore, the spot size (measured as the area of dense spot areas) decreased by approximately 63.7% after 40-Hz scintillation treatment for one week compared to the dark control (see, e.g., fig. 60A and 60C, p <0.01, by Mann Whitney test, n-8 mice/group). Taken together, these experiments identify a completely non-invasive treatment with a clear effect on amyloid plaque lesions.

To determine whether 40-Hz blinking improved another key AD-associated lesion, tau phosphorylation was studied using a tauopathy mouse model of TauP 301S. April-old TauP301S Tg mice (which at this age showed phosphorylated tau localized to the cell body) were treated daily for one hour for seven days using 40-Hz scintillation or dark control conditions. To examine how 40-Hz blinking alters tau phosphorylation, immunohistochemical characterization of the visual cortex was performed using three different epitopes for pTau (S202, S396 and S400/T403/S404; 11834S, 9632S, 11837S) and pTau antibody to dendritic marker MAP2 as a control.

Fig. 61A is a series of immunofluorescence images showing immunohistochemistry using anti-pTau 6102(S202) antibody and anti-MAP 26104 antibody in april-sized P301S mice after seven days of one hour/day under dark or 40-Hz scintillation conditions, according to some embodiments. Images were taken using a 40X objective (scale bar 50 μm; inset includes 100X renderings of representative cell bodies under dark and 40-Hz scintillation conditions). Fig. 61B is a bar graph depicting the relative pTau (S202) intensity levels of P301S visual cortex after seven days of one hour/day under dark and 40-Hz flash conditions according to some embodiments (n ═ 8 mice/group; one asterisk indicates P <0.05, by Student' S t-test). Figure 61C is a bar graph depicting relative MAP2 intensity levels of the P301S visual cortex after seven days of one hour/day under dark and 40-Hz light scintillation conditions according to some embodiments (n ═ 8 mice/group; "n.s." indicates non-significant, by Student's t-test). Fig. 61B and 61C show the mean values and SEM.

Fig. 62A is a series of immunofluorescence images (scale bar 50 μ ι η) showing immunohistochemistry using anti-pTau 6202(S404) antibody in 4-month old P301S mice after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments. Fig. 62B is a bar graph depicting relative pTau (S400/T403/S404) fluorescence intensity levels of P301S visual cortex after seven days of one hour/day under dark and 40-Hz flash conditions according to some embodiments (n ═ 8 mice/group; two asterisks indicate P <0.01, by Student' S T-test). Fig. 62B shows the mean values and SEM.

Fig. 63A is a series of immunofluorescence images (scale bar 50 μ ι η) showing immunohistochemistry using anti-pTau 6302(S396) antibody in april-sized P301S mice after seven days of one hour/day under dark and 40-Hz scintillation conditions, according to some embodiments. Fig. 63B is a bar graph depicting the relative pTau (S396) fluorescence intensity levels of the P301S visual cortex after seven days of one hour/day under dark and 40-Hz flash conditions, according to some embodiments (n ═ 8 mice/group; four asterisks indicate P <0.0001, by Student' S t-test).

The results show that in 40-Hz scintillation conditions, the signal intensity of pTau (S202) was reduced by 41.2% and the signal intensity of pTau (S400/T403/S404) was reduced by 42.3% (see, e.g., fig. 61A-fig. 61B, fig. 62A-fig. 62B, p <0.01, by Student' S T-test, n ═ 2 slices from 8 mice/group), while MAP2 levels were unchanged (see, e.g., fig. 61A and fig. 61C, "n.s." indicates non-significant, n ═ 2 slices from 4 mice/group) compared to the dark control. Staining with antibody against pTau (S396) showed the same directional trend: compared to the dark control, 40-Hz scintillation reduced the level of pTau (S396) by 14.4% (see, e.g., fig. 63A-63B, "n.s." indicating no significance, n ═ 2 sections from 8 mice/group). In addition, less mottle and cell body localization of pTau signal was observed in response to 40-Hz blinking compared to the dark control. Although a significant change in tau phosphorylation was seen, no discernible difference in the level of insoluble tau was observed between the 40-Hz scintillation-treated group and the dark control group.

The effect of 40-Hz scintillation on microglia in the TauP301S mouse model was evaluated. FIG. 64 is a series of immunofluorescence images showing immunohistochemistry using anti-IBa 1 (019-. Images were taken using a 40X objective (scale bar 50 μm; inset includes 100X renderings of representative microglia in EYFP and 40-Hz scintillation conditions).

Fig. 65A is a bar graph depicting the number of microglia after seven days of one hour/day under dark and 40-Hz blinking conditions, according to some embodiments (n 8 mice/group; "n.s." indicates non-significant, by Student's t-test). Figure 65B is a bar graph depicting the diameter of microglia cells normalized to a control after seven days of one hour/day under dark and 40-Hz blinking conditions according to some embodiments (n-8 mice/group; four asterisks indicate p <0.0001, by Student's t-test). Figure 65C is a bar graph depicting the average length of primary processes of microglia normalized to control after seven days of one hour/day under dark and 40-Hz blinking conditions, according to some embodiments (n ═ 8 mice/group; four asterisks indicate p <0.0001, by Student's t-test).

In some embodiments, microglia in the visual cortex of TauP301S mice are labeled with an anti-Iba 1 antibody after seven days of one hour per day 40-Hz blinking or dark conditions (see, e.g., fig. 64). In some embodiments, a trend toward a 29.50% increase in microglia number was observed in 40-Hz blinking conditions compared to dark controls (see, e.g., figure 64 and figure 65A, "n.s." indicates non-significant, n ═ 3 mice/group), consistent with observations made in the 5XFAD model (see, e.g., figure 50A). In addition, microglial body diameter increased by 49.00% after 40-Hz blinking compared to the dark control (see, e.g., figure 64 and figure 65B, p <0.0001, by Student's t-test, n-3 mice/group). The length of microglia primary process was reduced by 39.08% in the 40-Hz scintillation group compared to the dark control (see, e.g., figure 64 and figure 65C, p <0.0001, by Student's t-test, n-3 mice/group).

Taken together, these data from multiple models of AD lesions and in WT animals demonstrate that 40-Hz oscillation can mitigate amyloid lesions (as measured by a decrease in a β levels) and can reduce tau phosphorylation. Furthermore, 40Hz visual flicker can drive different morphological transformations of microglia in both amyloidosis and tauopathy models of AD lesions.

In another experiment, a subset of aged mice (i.e., june old) were exposed to visual gamma stimulation for seven days. The remaining mice were kept in the dark. Fig. 66 is a graph showing the levels of both soluble a β peptide and insoluble a β peptide (i.e., plaques) in the visual cortex of mice. As shown in FIG. 66, soluble isoform A β _1-40 6600. Soluble isoform a β _1-42 6602. Insoluble isoform of A beta _1-40 6604. And insoluble isoform of A beta _1-42 6606 the level of each is significantly reduced in mice exposed to visual gamma stimulation.

Fig. 67A-67B are graphs showing Α β peptide levels in subjects with and without transcranial gamma stimulation, according to some embodiments. In fig. 67A, whole brain Α β peptide levels remained unchanged without stimulation 6700, but decreased after one hour of transcranial γ stimulation 6702 (n-1 animal/group). In fig. 67B, whole brain Α β peptide levels decreased after 40z transcranial stimulation at hippocampus 6704 and at cortex 6706 of 5xFAD mice, according to some embodiments.

Gamma oscillations have long been associated with higher cognitive function and sensory response. In some embodiments, the driving of FS-PV-interneurons using the optogenetic approach enhances LFP at 40Hz in mice. As disclosed herein, it has been demonstrated that in some embodiments, the use of optogenetic or non-invasive photoscintigraphy to drive 40-Hz oscillations and phase-lock spikes in a 5XFAD mouse model causes a significant reduction in a β peptide in at least two different brain regions. This reduction is not due to reduced spiking activity, as the Α β peptide level is significantly lower in response to 40-Hz stimulation than in response to random stimulation conditions that produce similar amounts of multi-unit spiking activity without enhancing 40-Hz oscillations. The pyramidal cell firing rate may vary between these conditions, but the firing of FS-PV-interneurons or other cell types masks this change. In some embodiments, the stochastic optogenetic stimulation of the FS-PV-interneuron provides the same amount of direct stimulation of the FS-PV-interneuron, but does not reduce amyloid. In fact, optogenetic random stimulation increased amyloid levels by more than three times without significant changes in random visual flicker, which may indicate that some aspects of random stimulation have neurotoxic effects. While in some embodiments, random stimulation did not result in increased gamma power, a trend of a small increase in power was noted in a wide range of frequencies (about 20Hz to greater than 60 Hz). In some embodiments, a trend of increased amyloid levels in the case of 20-Hz and 80-Hz light scintillation was noted. Taken together, these results may indicate that driving activity at some frequencies below or above 40Hz may increase amyloid levels. These results point to the need to understand how the pattern of spike activity affects molecular pathways and disease lesions.

Robust reduction of total amyloid levels may be mediated by reduced amyloidogenesis, involving a reduction of EEA1/Rab 5-positive early endosomes and increased endocytosis of amyloid by microglia. Importantly, The Gene Set Enrichment Analysis (GSEA) statistical analysis disclosed herein (The Broad Institute, Cambridge, Massachusetts) showed that The classical macrophage pro-inflammatory M1 or anti-inflammatory M2 cell state was not associated with up-or down-regulated gene expression profiles following neuronal stimulation by 40-Hz oscillation. In fact, the expression levels of pro-inflammatory genes Il6, Il1b, Itgam and anti-inflammatory gene Igf1 did not change after stimulation. In contrast, microglial phagocytosis-promoting genes and the number of cell adhesion/migration regulator Spp1 were activated after 40-Hz stimulation. Thus, it appears that driving 40Hz gamma oscillations induces an overall neuroprotective response by recruiting both neurons and microglia. The fact that GABA-a antagonist treatment completely abolished the effect of 40-Hz stimulation on lowering Α β levels strongly suggests that gabaergic signaling (most likely involving FS-PV-interneurons) is critical for these effects. Furthermore, in some embodiments, 40-Hz scintillation stimulation reduces a β in a variety of mouse models, including APP/PS1 and WT mice in addition to 5XFAD mice. This duplication in various mouse models shows that these findings may not be specific for one animal model and importantly, extends to the case where APP is expressed through its physiological promoter and a β is produced from endogenous APP, as in WT animals. Furthermore, in some embodiments, 40-Hz oscillation was found to reduce pTau in a mouse model of tauopathy TauP301S, showing that the protective effects of gamma stimulation are generalized not only to other mouse models, but also to other pathogenic proteins. In summary, the findings disclosed herein reveal previously unknown cellular and molecular processes mediated by gamma oscillation and establish functional relationships between brain gamma rhythm, microglial function and AD-related pathologies. In some embodiments, the discovery of gamma oscillation defects is summarized with evidence of gamma defects in different mouse models of AD (hAPP and apoE4) and reported that gamma is altered in humans with AD. By looking for a summary of evidence from various mouse models of AD, including Tg and knock-in models, it can be demonstrated that these results are not only due to expression of the transgene or to other side effects specific to one model. Together, these results from mice and humans show that multiple molecular pathways contributing to Α β lesions collectively alter γ oscillations in AD. The findings disclosed herein hold the promise of novel therapeutic interventions against AD.

One theory of the etiology of AD points to the failure of microglial function (specifically, the inability of microglia to clear pathological molecules) as a key mechanism in disease progression. Thus, interventions that restore microglia to endocytic state (as done by 40-Hz stimulation) have strong therapeutic potential. In experiments described further herein, driving gamma oscillations optogenetically or by light scintillation does not result in too strong activity of neurons. Since this approach is fundamentally different from previous AD therapies, driving this pattern of neural activity to trigger endogenous repair would provide a novel therapeutic approach to AD.

Visual stimuli at gamma frequencies have a positive effect on the behavior of the subject.

A study was conducted to examine whether gamma exposure and/or administration according to some embodiments resulted in any stress to the subject. Figure 68A is a flow chart showing the study. As shown at 6800 in figure 68A, WT mice were exposed to normal indoor lighting (N ═ 8) or 40-Hz light flashes (N ═ 8) for one hour/day for seven consecutive days, days 1 to 7, according to some embodiments. On day 8, blood was collected from the mice and plasma was isolated to check corticosterone levels, as shown at 6802. In mice, corticosterone is the major glucocorticoid involved in stress response.

Figure 68B is a bar graph depicting the levels of Corticosterone (CORT) (pg/ml) in plasma collected from eight mice exposed to Normal Room Light (NRL) and eight mice exposed to 40-Hz light flashes (40-Hz). No increase in corticosterone was observed in mice exposed to 40-Hz light flashes. In contrast, the group of mice exposed to 40-Hz light flashes had lower levels of corticosterone than the control group. For N-8 independent measurements/group, the T-distribution and p-value of corticosterone levels were calculated as:

T(14)＝0.827；p＝0.422 (1)

another study was conducted to examine whether gamma exposure and/or administration according to some embodiments reduces anxiety in a subject. Figure 68A is a flow chart showing the study. As shown at 6900 in fig. 69A, WT mice were exposed to normal indoor lighting (N ═ 10) or 40-Hz light flashes (N ═ 10) for one hour/day for seven consecutive days, days 1 to 7, according to some embodiments. On day 8, shown at 6902, a ten minute conversation of the elevated plus maze was conducted.

The elevated plus maze is a test used to measure anxiety in laboratory animals. The behavioral patterns are based on the general aversion of rodents to open spaces, which results in thigmotaxis, a preference for remaining in an enclosed space or near the edges bounding the space. Fig. 69B is an image showing an elevated plus labyrinth device. The device is cross-shaped with two open arms (vertical) and two closed arms (horizontal). Anxiety is expressed by the animals spending more time in the closed arms.

Fig. 69C and 69D are images showing representative trajectories of subjects during an elevated plus maze session. According to some embodiments, in fig. 69C, mice exposed to normal indoor lighting tended to stay in the closed arm, indicating more anxiety, while in fig. 69D, mice exposed to 40-Hz light flashes were explored in both the open arm and the closed arm, indicating relatively less anxiety.

Figure 70 is a bar graph depicting the total time spent exploring the open and closed arms by ten mice exposed to normal indoor lighting (NRL) and ten mice exposed to 40-Hz light flashes (40-Hz), according to some embodiments. According to some embodiments, mice exposed to 40-Hz light flashes spend less total time in the closed arm and more total time in the open arm compared to the control group, indicating less anxiety. For N-10 independent measurements/set, the T-distribution and p-value of the total time spent exploring the closure arm were calculated as:

T(18)＝-1.652；p＝0.11 (2)

for N-10 independent measurements/set, the T-distribution and p-value of the total time spent on exploring the open arm were calculated as:

T(18)＝-2.136；p＝0.047 (3)

another study was conducted to examine whether gamma exposure and/or administration according to some embodiments reduces stress and/or anxiety in a subject. Figure 71A is a flow chart showing the study. At 7100 in fig. 71A, WT mice were exposed to normal indoor lighting (N-8) or 40-Hz light flashes (N-8) for one hour/day for seven consecutive days, day 1-day 7, according to some embodiments. On day 8, shown at 7102, a five minute open field test was performed.

Experiments to determine the level of general locomotor activity and anxiety in laboratory mice at the time of open field testing. The behavioral patterns are based on anxiety caused by rodents avoiding brightly lit areas, yet exploring conflicting desires for perceived dangerous stimuli. Fig. 71B is an image showing an open field site. Open field sites have walls that prevent escape and can be monitored using grid markers or using infrared beams or cameras integrated with software systems. According to some embodiments, increased anxiety will result in less motor activity and preference for the edges of the scene, while decreased anxiety results in increased exploratory behavior.

Fig. 71C and 71D are images showing representative trajectories of subjects during open field testing. According to some embodiments, in fig. 71C, mice exposed to normal indoor lighting tended to prefer the edges of the venue, indicating more stress and/or anxiety, while in fig. 71D, mice exposed to 40-Hz light flashes were explored more in the center of the venue, indicating relatively less stress and/or anxiety.

Fig. 72A and 72B are graphs depicting the total time spent exploring the center and edges of an open field venue by eight mice exposed to normal indoor lighting (NRL) and eight mice exposed to 40-Hz light flashes (40-Hz), according to some embodiments. Fig. 72A is a graph of the average amount of seconds spent at the center of the field for each minute of five minutes. Figure 72B is a bar graph of the total time spent at the edge of the field for the entire five minute duration (on average per minute).

On average, mice exposed to 40-Hz light flashes spent more time in the center of the field, significantly during

minutes

2, 4, and 5, indicating less stress and/or anxiety than the control group, which is also consistent with elevated plus maze results according to some embodiments. Repeated measures analysis of variance (RM ANOVA) was performed. For N-8 independent measurements/group, the F distribution and p value of the average time spent exploring the open field site were calculated as:

F(1,14)＝4.860；p＝0.045 (4)

another study was conducted to examine whether gamma exposure and/or administration according to some embodiments alters the subject's inherent novelty seeking behavior. Fig. 73A and 73B are schematic diagrams showing a study using a novel recognition task. In fig. 73A, two new items are provided in a familiar venue. In fig. 73B, a familiar item and a new item are provided in a familiar venue. According to some embodiments, wild-type mice are exposed to normal indoor light (N-8) or 40-Hz light flashes (N-8) for one hour/day for seven consecutive days, day 1-day 7.

On day 8, mice were exposed to the scenario in fig. 73A, two new items in a familiar field for five minutes. Figure 73C is a bar graph depicting the percentage of time spent exploring new item a versus the percentage of time spent exploring new item B for eight mice exposed to Normal Room Lighting (NRL) and eight mice exposed to 40-Hz light flashes (40-Hz), according to some embodiments. As shown in fig. 73C, each group shows equal preference for each item. I.e. no differences in item exploration were observed between the groups.

The mice were then exposed to the scenario in fig. 73B, one familiar item and one novel item in a familiar field, for five minutes. Fig. 74 is a graph depicting the average amount of seconds spent exploring a new item for each of the five minutes. On average, according to some embodiments, mice exposed to 40-Hz light flashes spent a significantly greater amount of time exploring new items, particularly during minutes 1-3 and 5, indicating increased novelty seeking behavior compared to the control group. Friedman non-parametric RM ANOVA was performed. Test statistic χ of average time spent exploring a novel item for N8 independent measures/group ² And the p-value is calculated as:

χ ² (4,n＝16)＝16.088；p＝0.003 (5)

the Mann-Whitney U test was performed for the average time spent exploring the new item during the 3 rd minute. For N-8 independent measurements/set, the U, Z and p values were calculated as:

U＝58.00；Z＝2.731；p＝0.005 (6)

another study was conducted to examine whether gamma exposure and/or administration according to some embodiments affects learning and memory of the subject. Figure 75A is a flow chart showing a study using the fear conditioned reflex paradigm. As shown at 7500 in figure 75A, WT mice were exposed to normal indoor lighting or 40-Hz light flashes for one hour/day for seven consecutive days, day 1-day 7, according to some embodiments. On day 8, mice were subjected to a moderate two-tone-shock pairing, shown at 7502. Specifically, the mouse was introduced into a new field, where the first tone was paired with a foot shock. The mouse makes a conditioned reflex to correlate the environment (i.e., tone) with an aversive experience (i.e., foot shock). For this initial environment, the T distribution and p value of the total time spent on stiffness (fleeing) is calculated as:

T(24)＝0.577；p＝0.569 (7)

On day 9, a tone test was conducted in a changed environment, shown at 7504. Fig. 75B is a stimulus diagram showing a tone test as a function of time, including a first tone environment 7506, a first post-tone environment 7508, a second tone environment 7510, and a second post-tone environment 7512. For the test, the mice were returned to the field where the first tone paired with a leg shock. When the first tonal environment 7506 is applied, mice exposed to 40-Hz light flashes spend more time rigor and may be expecting a foot shock, indicating memory behavior. Mice exposed to 40-Hz light flashes also spent more time on rigidity during the second tonal environment 7510, but less time on rigidity during the post-tonal environment compared to the control group.

Fig. 76A and 76B are bar graphs demonstrating enhanced memory according to some embodiments. As shown in figure 76A, according to some embodiments, a greater percentage of time spent on rigor during first and second

tonal environments

7506, 7510 is compared to the control group for mice exposed to 40-Hz light flashes, indicating an enhanced memory association. Furthermore, according to some embodiments, mice exposed to 40-Hz light flashes exhibited a stronger fear presentation after the tone subsided. As shown in figure 76B, according to some embodiments, a greater percentage of time spent on rigor during the first post-tone environment 7506 and the second post-tone environment 7510 was compared to mice exposed to 40-Hz light flashes for the control group, indicating enhanced memory specificity.

For the pre-tonal environment, RM ANOVA was performed between groups and the F-distribution and p-value of the mean time spent on rigor is calculated as:

F(1,24)＝3.106；p＝0.091 (8)

for the first tonal environment, the T-distribution and p-value of the total time spent on rigor is calculated as:

T(24)＝-2.155；p＝0.041 (9)

for the second tonal environment, the T-distribution and p-value of the total time spent on rigor is calculated as:

T(24)＝-1.433；p＝0.164 (10)

for tonal environments, RM ANOVA was performed between groups and the F distribution and p value of the mean time spent on rigor is calculated as:

F(1,24)＝4.559；p＝0.043 (11)

for the first post-tonal environment, the T-distribution and p-value of the total time spent on the rigor is calculated as:

T(24)＝1.874；p＝0.073 (12)

for the second post-tonal environment, the T-distribution and p-value of the total time spent on the stiffness are calculated as:

T(24)＝2.223；p＝0.036 (13)

for the post-tonal environment, RM ANOVA was performed between groups and the F-distribution and p-value of the mean time spent on rigor is calculated as:

F(1,24)＝6.646；p＝0.017 (14)

another study was conducted to examine whether gamma exposure and/or administration according to some embodiments improves the subject's memory. Figure 77A is a flow chart showing the study. As shown at 7700 in figure 77A, WT mice were exposed to normal indoor lighting or 40-Hz light flashes for one hour/day for seven consecutive days, day 1-day 7, according to some embodiments. On day 8, shown at 7702, the Morris water maze test was performed.

The Morris water navigation task or maze is a test used to study spatial memory and learning in laboratory mice. The behavioral program involved placing the subject in a macro-shaped pool with an invisible or visible platform that allowed the subject to escape the water using either a praxic strategy (remembering the movements needed to reach the platform), a taxi strategy (using visual cues to locate the platform), or a spatial strategy (using distance cues as reference points). Fig. 77B is a diagram showing the Morris water maze. The maze comprises a circular pool with water divided into directional quadrants and a platform 7704 hidden in the Southwest (SW) quadrant.

For weak training, the Morris water maze test was repeated twice daily for four consecutive days, days 8-11. Figure 78A is a graph depicting the delay in finding a platform from mice exposed to normal indoor lighting (NRL) and mice exposed to 40-Hz light flashes (40-Hz), according to some embodiments.

On day 12, probing tests were performed by removing the hidden platform from the Morris water maze. Fig. 77C and 77D are images showing representative trajectories of subjects during the probing test. In fig. 77C, mice exposed to normal indoor lighting appeared to find the platform through the entire pool, while in fig. 77D, mice exposed to 40-Hz light flashes appeared to find more methodically and primarily in the SW quadrant, according to some embodiments. Fig. 78B is a graph depicting the total time (number of seconds per half minute) spent looking for a platform in the target quadrant (i.e., SW quadrant), while fig. 78C is a graph depicting the total time (number of seconds per half minute) spent looking for a platform in the opposite quadrant (i.e., NE quadrant). According to some embodiments, mice exposed to 40-Hz light flashes spend more time looking for in the target quadrant than the control group and less time looking for in the opposite quadrant than the control group, indicating an increase in spatial memory.

Reverse learning was performed using the same group of mice from both the Morris water maze test and the probe test. Fig. 79A is a diagram showing a Morris water maze hiding the platform 7900 in the SW quadrant as in the described experiment. Fig. 79B is a diagram showing a Morris water maze hiding the platform 7902 in the opposite NE quadrant for reverse learning.

For weak training, reverse learning was repeated twice daily for four consecutive days, day 14-day 17. Figure 79C is a graph depicting the delay in finding a platform from mice exposed to normal indoor lighting (NRL) and mice exposed to 40-Hz light flashes (40-Hz), according to some embodiments. Mice exposed to 40-Hz light flashes still showed increased behavioral flexibility, although they received no additional 40-Hz exposure after day 7.

Another study was conducted to examine whether chronic gamma exposure and/or administration according to some embodiments affects spatial learning and memory in subjects. Figure 80A is a flow chart showing the study. As shown at 8000 in figure 80A, according to some embodiments, C57BL/6 mice were exposed to normal room light (N ═ 7) or 40-Hz light flashes (N ═ 7) for one hour/day for two weeks. During the third week, mice continued to be exposed to normal indoor lighting or 40-Hz light flashes for one hour each morning and then also to the Morris water maze test each afternoon, as shown at 8002.

Figure 80B is a graph depicting the delay in finding a platform from mice exposed to normal indoor lighting (NRL) and mice exposed to 40-Hz light flashes (40-Hz) on days 1-4 of the third week. After the third week, probe tests were conducted by removing the hidden platform. FIG. 80C is a bar graph depicting the total time (seconds per 30 second trial) spent looking for a platform in the target quadrant during the probing test. According to some embodiments, similar to one week treatment, chronic three week treatment enhances spatial learning.

Reverse learning was performed using the same group of mice from fig. 80A-80C. Fig. 81A is a flowchart showing an extended study. As shown at 8100 in figure 81A, C57BL/6 mice were exposed to normal indoor lighting or 40-Hz light flashes for one hour/day for two weeks according to some embodiments. During the third week, mice continued to be exposed to normal indoor lighting or 40-Hz light flashes for one hour each morning and then also to the Morris water maze test each afternoon, as shown at 8102. During the fourth week, mice continued to be exposed to normal room lighting or 40-Hz light flashes for one hour each morning and then also to the Morris water maze reversal test each afternoon, as shown at 8104. Figure 81B is a graph depicting the delay in finding a platform from mice exposed to normal indoor lighting (NRL) and mice exposed to 40-Hz light flashes (40-Hz) on days 1-4 of the fourth week, according to some embodiments.

After the fourth week, probe testing is performed by removing the hidden platform. FIG. 82A is a bar graph depicting the total time (seconds per 30 second trial) spent looking for a platform in the target quadrant during a probing test. FIG. 82B is a bar graph depicting the time spent in the opposite quadrant during probe testing. Mice exposed to 40-Hz light scintillation showed greater cognitive flexibility.

Visual stimulation at gamma frequencies provides anatomical, morphological, cellular, and molecular benefits.

Studies were conducted to examine the effects of gamma exposure and/or administration according to some embodiments on DNA damage and neuronal loss in the visual cortex of a subject. For the study, an inducible mouse model of p25 accumulation (i.e., creatine kinase-carboxy terminal fragment p25 Tg mouse (CK-p25 Tg mouse)) was used. The CK-p25 Tg mouse model shows key pathological hallmarks of AD, including significant neuronal loss in the forebrain, increased a β peptide production, tauopathy, DNA damage, and severe cognitive impairment. In this model, increased a β peptide production was observed prior to neuronal loss; furthermore, decreasing Α β peptide production alleviates memory deficits in the CK-p25 Tg mouse model, indicating that this event acts synergistically with the carboxy-terminal fragment p25, leading to the manifestation of neurodegeneration and dysmnesia.

Figure 83 is a timeline diagram 8300 showing changes in CK-p25 Tg mice. At 8302 after two weeks, the mice exhibited DNA damage (e.g., biomarker γ H2AX), increased a β peptide, and microglial activation. At 8304 after six weeks, the mice exhibited synaptic loss, neuronal loss, tau hyperphosphorylation, defects in long-term potentiation, and memory impairment.

A study was conducted to compare groups of mice under different treatment protocols. Figure 84 is a graph of groups including CK control mice 8400, non-treated CK-p25 Tg mice 8402, CK-p25 Tg mice 8404 treated with memantine (10mg/kg daily), CK-p25 Tg mice 8406 exposed to 40-Hz light flashes (one hour per day for 6 weeks) according to some embodiments, and CK-p25 Tg mice 8408 treated with memantine and also exposed to 40-Hz light flashes. Memantine is a drug with limited success for the treatment of severe AD by blocking NMDA receptors and thereby acting on the glutamatergic system.

Gamma exposure and/or administration according to some embodiments is shown to protect and/or reduce changes in brain anatomy. For example, gamma exposure reduces and/or prevents CKp-25-induced loss of brain weight. Figure 85 is a bar graph comparing brain weight change in the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Brain weight loss was evident in non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. However, CK-p25 Tg mice exposed to 40-Hz light flashes according to some embodiments retained more brain weight.

Gamma exposure and/or administration according to some embodiments is shown to protect brain morphology and/or reduce changes in brain morphology. For example, gamma exposure reduces and/or prevents CKp-25-induced abnormal lateral ventricle dilation in a subject. Fig. 86 is a bar graph comparing fold change in lateral ventricle dilation for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation, with the expansion of CK control mice as baseline. Lateral ventricular dilatation was evident in non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. The lateral ventricles of CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments were less distended than the lateral ventricles of other CK-p25 Tg mice.

Fig. 87A-87E are images showing the lateral ventricles of subjects representing each group. Lateral ventricles were greatest in non-treated CK-p25 Tg mice (fig. 87A), CK-p25 Tg mice treated with memantine (fig. 87B), and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation (fig. 87C). As shown in fig. 87D, CK-p25 Tg mice exposed to 40-Hz light flashes according to some embodiments had far less lateral ventricular expansion. Fig. 87E is an example of baseline lateral ventricle size in CK control mice.

Fig. 88A-88C are brain anatomical diagrams showing brain regions of interest for molecular characterization, according to some embodiments. Figure 88A includes visual skin layer (V1)8800, somatosensory skin layer (SS1)8802, hippocampus 8804, and island leaf skin layer 8806.

Gamma exposure and/or application according to some embodiments is shown to protect and/or reduce alterations of cortical and neuronal layers in the visual cortex. For example, gamma exposure reduces and/or prevents CKp-25-induced cortical and neuronal layer loss in the visual cortex of a subject.

Nuclear staining with Hoechst markers (i.e., blue fluorescent dye used to stain DNA) was used to gauge cortical layer loss. NeuN (a neuronal nuclear antigen commonly used as a biomarker for neurons) is used to gauge neuronal layer loss. Fig. 89 is a bar graph depicting the average thickness of V1-cortical layer in each group, and fig. 90 is a bar graph depicting the average thickness of V1-NeuN-positive cell layer in each group.

Fig. 91A-fig. 91E are images showing cells with Hoechst markers and/or NeuN markers representing subjects of each group. FIG. 91A is an example of the thickness of the baseline V1-cortical (e.g., 837. + -. 9. mu.M) and V1-neuronal (e.g., 725. + -. 7. mu.M) layers of CK control mice.

V1-the cortical layer was gradually thinned in the following mice: CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments (figure 91D, e.g., 855 ± 9 μ M); CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation (FIG. 91E, e.g., 821. + -. 22. mu.M); non-treated CK-p25 Tg mice (fig. 91B, e.g., 792 ± 13 μ M); and CK-p25 Tg mice treated with memantine (fig. 91C, e.g., 788 ± 9 μ M).

The V1-neuron layer was actually thicker in CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments than in CK control mice (fig. 91D, e.g., 743 ± 9 μ M), but then progressively thinner in the following mice than in CK control mice: CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation (FIG. 91E, e.g., 691. + -. 20 μ M); non-treated CK-p25 Tg mice (fig. 91B, e.g., 666 ± 14 μ M); and CK-p25 Tg mice treated with memantine (fig. 91C, e.g., 660 ± 7 μ M).

Gamma exposure and/or administration according to some embodiments is shown to protect and/or reduce alterations of cortical and neuronal layers in the somatosensory cortex. For example, gamma exposure reduces and/or prevents CKp-25-induced cortical and neuronal layer loss in the somatosensory cortex of a subject.

Fig. 92 is a bar graph depicting the average thickness of the SS 1-cortical layer in each group, and fig. 93 is a bar graph depicting the average thickness of the SS 1-NeuN-positive cell layer in each group.

Fig. 94A-94E are images showing cells with Hoechst markers and/or NeuN markers representative of subjects of each group. FIG. 94A is an example of the thickness of the baseline SS 1-cortical (e.g., 846 + -10 μ M) and SS 1-neuronal (e.g., 707 + -8 μ M) layers of CK control mice.

SS 1-cortical layer was gradually thinned in the following mice: CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments (fig. 94D, e.g., 834 ± 9 μ M); CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation (fig. 94E, e.g., 778 ± 13 μ M); non-treated CK-p25 Tg mice (fig. 94B, e.g., 762 ± 17 μ M); and CK-p25 Tg mice treated with memantine (fig. 94C, e.g., 756 ± 11 μ M).

The SS 1-neuron layer of CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments was nearly the same thickness as the SS 1-neuron layer of CK control mice (fig. 94D, e.g., 705 ± 15 μ M). However, the SS 1-neuron layer gradually thinned in the following mice: CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation (FIG. 94E, e.g., 650. + -.11. mu.M); non-treated CK-p25 Tg mice (fig. 94B, e.g., 630 ± 13 μ M); and CK-p25 Tg mice treated with memantine (fig. 94C, e.g., 629 ± 9 μ M).

Gamma exposure and/or application according to some embodiments is shown to protect and/or reduce alterations of cortical and neuronal layers in the islet cortex layers. For example, gamma exposure reduces and/or prevents CKp-25-induced cortical and neuronal layer loss in the islet cortex of a subject.

Fig. 95 is a bar graph depicting the average thickness of the cortex layer of the island cortex in each group, and fig. 96 is a bar graph depicting the average thickness of the NeuN-positive cell layer of the island cortex in each group.

Fig. 97A-97E are images showing cells with Hoechst markers and/or NeuN markers representing subjects of each group. Fig. 97A is an example of the thickness of the baseline cortical layer (e.g., 1134 ± 10 μ M) and neuronal layer (e.g., 1010 ± 11 μ M) of the islet cortex of CK control mice.

The cortex was tapered in the islet cortex of the following mice: CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments (fig. 97D, e.g., 1079 ± 20 μ M); CK-p25 Tg mice treated with memantine (fig. 97C, e.g., 983 ± 12 μ M); CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation (fig. 97E, e.g., 965 ± 16 μ M); and non-treated CK-p25 Tg mice (fig. 97B, e.g., 764 ± 27 μ M).

Neuronal layers were progressively thinner in the islet cortex of the following mice: CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments (fig. 97D, e.g., 953 ± 17 μ Μ); non-treated CK-p25 Tg mice (fig. 97B, e.g., 861 ± 30 μ M); CK-p25 Tg mice treated with memantine (fig. 97C, e.g., 850 ± 18 μ M); and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation (fig. 97E, e.g., 848 ± 15 μ M).

Changes in the number of and/or reducing the number of neurons and/or lesions of DNA are shown for gamma exposure and/or administration according to some embodiments. For example, gamma exposure reduces CKp-25-induced neuronal loss and DNA damage in the visual cortex of a subject.

Fig. 98 is a bar graph comparing the amount of NeuN-positive cells as a percentage of NeuN-positive cells in CK control mice for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Thus, the percentage of NeuN-positive cells in CK control mice was 100% in CK control mice, but only about 80% in non-treated CK-p25 Tg mice, confirming neuronal loss in the CK-p25 Tg mouse model. Treatment with memantine prevented some neuronal loss in CK-p25 Tg mice compared to the non-treated group. Exposure to 40-Hz light flashes according to some embodiments prevented the most neuronal loss in CK-p25 Tg mice. Thus, fig. 98 shows how a 40-Hz visual flicker process according to some embodiments can protect neurons in the visual cortex. However, the combination of memantine and exposure to 40-Hz light flashes did not prevent as much neuronal loss.

DNA Double Strand Breaks (DSBs) are an example of DNA damage in eukaryotic cells that leads to genomic instability, thereby triggering tumorigenesis and possibly accelerated aging. Phosphorylated histone H2AX (γ H2AX) was used as a biomarker for cellular response to DSBs. Fig. 99 is a bar graph comparing the amount of γ H2 AX-positive cells in the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Cells positive for γ H2AX were almost absent in CK control mice but very high in non-treated CK-p25 Tg mice, indicating a large amount of DSB and other DNA damage. Treatment with memantine reduced the amount of γ H2 AX-positive cells in CK-p25 Tg mice compared to the non-treated group. Exposure to 40-Hz light scintillation according to some embodiments caused an even greater reduction in γ H2 AX-positive cells in CK-p25 Tg mice. Thus, figure 99 shows how a 40-Hz visual flicker treatment according to some embodiments can reduce DNA damage in the visual cortex. However, the combination of memantine and exposure to 40-Hz light flashes significantly increased the number of γ H2 AX-positive cells in CK-p25 Tg mice.

Panel 100 is a series of images showing visual cortex samples labeled with Hoechst stain (indicative of cortical cells), green fluorescent protein or GFP (indicative of CK-p25), γ H2AX (indicative of DSB), or NeuN (indicative of neurons) representative of subjects of each group.

Gamma exposure also reduces CKp-25-induced neuronal and DNA damage in the somatosensory cortex of the subject. Figure 101 is a bar graph comparing the amount of NeuN-positive cells as a percentage of NeuN-positive cells in CK control mice for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Thus, the percentage of NeuN-positive cells in CK control mice was 100% in CK control mice, but closer to 80% in non-treated CK-p25 Tg mice, confirming neuronal loss in the CK-p25 Tg mouse model. Treatment with memantine did not prevent any neuronal loss in CK-p25 Tg mice compared to the non-treated group, except for the combination with exposure to 40-Hz light flashes, which prevented the most neuronal loss in CK-p25 Tg mice. Thus, fig. 101 shows how a 40-Hz visual flicker treatment according to some embodiments can protect neurons in the somatosensory cortex.

Fig. 102 is a bar graph comparing the amount of γ H2 AX-positive cells in the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Cells positive for γ H2AX were not present in CK control mice, but were very high in non-treated CK-p25 Tg mice, indicating a large amount of DSB and other DNA damage. Treatment with memantine reduced the amount of γ H2 AX-positive cells in CK-p25 Tg mice compared to the non-treated group. Exposure to 40-Hz light scintillation according to some embodiments caused an even greater reduction in γ H2 AX-positive cells in CK-p25 Tg mice. Thus, figure 102 shows how a 40-Hz visual flicker treatment according to some embodiments can reduce DNA damage in the somatosensory cortex. However, the combination of memantine and exposure to 40-Hz light flashes significantly increased the number of γ H2 AX-positive cells in CK-p25 Tg mice.

Figure 103 is a series of images showing somatosensory cortical samples labeled with NeuN (indicating neurons), γ H2AX (indicating DSBs), GFP (indicating CK-p25), and/or Hoechst stain (indicating cortical cells) representative of subjects in each group.

Gamma exposure also reduces CKp-25-induced neuronal and DNA damage in the islet cortex of the subject. Fig. 104 is a bar graph comparing the amount of NeuN-positive cells as a percentage of NeuN-positive cells in CK control mice for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Thus, the percentage of NeuN-positive cells in CK control mice was 100% in CK control mice, but closer to 80% in non-treated CK-p25 Tg mice, confirming neuronal loss in the CK-p25 Tg mouse model. Treatment with memantine prevented some neuronal loss in CK-p25 Tg mice compared to the non-treated group, except for the combination with exposure to 40-Hz light flashes, which prevented minimal neuronal loss in CK-p25 Tg mice. Thus, fig. 104 shows how a 40-Hz visual flicker process according to some embodiments can protect neurons in the island cortex.

Fig. 105 is a bar graph comparing the amount of γ H2 AX-positive cells in the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Cells positive for γ H2AX were not present in CK control mice, but were very high in non-treated CK-p25 Tg mice, indicating a large amount of DSB and other DNA damage. Treatment with memantine reduced the amount of γ H2 AX-positive cells in CK-p25 Tg mice compared to the non-treated group. Exposure to 40-Hz light scintillation according to some embodiments caused a similar reduction in γ H2 AX-positive cells in CK-p25 Tg mice. Thus, figure 105 shows how a 40-Hz visual flicker treatment according to some embodiments can reduce DNA damage in the island cortex. However, the combination of memantine and exposure to 40-Hz light flashes significantly increased the number of γ H2 AX-positive cells in CK-p25 Tg mice.

Panel 106 is a series of images showing islet cortex samples labeled with NeuN (indicating neurons), γ H2AX (indicating DSBs), GFP (indicating CK-p25), or Hoechst stain (indicating cortical cells) representative of subjects in each group.

Gamma exposure also reduces CKp-25-induced neuronal loss and DNA damage in the hippocampus of the subject. Figure 107 is a bar graph comparing the amount of NeuN-positive cells as a percentage of NeuN-positive cells in CK control mice for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Thus, the percentage of NeuN-positive cells in CK control mice was 100% in CK control mice, but closer to 80% in non-treated CK-p25 Tg mice, confirming neuronal loss in the CK-p25 Tg mouse model. Treatment with or without memantine exposure to 40-Hz light scintillation prevented some neuronal loss in CK-p25 Tg mice compared to the non-treated group, which prevented minimal neuronal loss in CK-p25 Tg mice. Thus, fig. 107 shows how 40-Hz visual flicker processing according to some embodiments can protect neurons in the hippocampus.

Figure 108 is a bar graph comparing the amount of γ H2 AX-positive cells in the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation. Cells positive for γ H2AX were not present in CK control mice, but were very high in non-treated CK-p25 Tg mice, indicating a large amount of DSB and other DNA damage. Treatment with memantine reduced the amount of γ H2 AX-positive cells in CK-p25 Tg mice compared to the non-treated group. Exposure to 40-Hz light scintillation according to some embodiments caused a better reduction of γ H2 AX-positive cells in CK-p25 Tg mice. Thus, figure 108 shows how a 40-Hz visual flicker treatment according to some embodiments can reduce DNA damage in hippocampus. However, the combination of memantine and exposure to 40-Hz light flashes significantly increased the number of γ H2 AX-positive cells in CK-p25 Tg mice.

Fig. 109 is a series of images showing hippocampal samples labeled with Hoechst stain (indicating cortical cells), GFP (indicating CK-p25), γ H2AX (indicating DSBs), or NeuN (indicating neurons) representing subjects of each group.

Gamma exposure and/or administration is shown to protect synapses and/or reduce synapse loss according to some embodiments. Changes in synaptic connectivity can be quantified using specific markers for glutamatergic synapses (e.g., VGluT1, VGluT2, PSD95, and GluR2) and specific markers for gabaergic synapses (e.g., GAD and VGAT).

For example, gamma exposure reduces CKp-25-induced synaptic loss in the visual cortex of the subject. FIG. 110 is a bar graph comparing stain density for glutamatergic synapses (using VGluT1) and gabaergic synapses (using GAD65) as a percentage of baseline synaptic stain density in CK control mice for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz photoscintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz photoscintillation.

Gamma exposure also reduces CKp-25-induced synaptic loss in the somatosensory cortex of the subject and even increases synaptic stain density. FIG. 111 is a bar graph comparing stain density for glutamatergic synapses (using VGluT1) and GABAergic synapses (using GAD65) as a percentage of baseline synaptic stain density in CK control mice for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation.

Gamma exposure also reduced CKp-25-induced synaptic loss in the islet cortex of the subject. FIG. 112 is a bar graph comparing stain density for glutamatergic synapses (using VGluT1) and GABAergic synapses (using GAD65) as a percentage of baseline synaptic stain density in CK control mice for the following mice: CK control mice, non-treated CK-p25 Tg mice, CK-p25 Tg mice treated with memantine, CK-p25 Tg mice exposed to 40-Hz light scintillation according to some embodiments, and CK-p25 Tg mice treated with both memantine and 40-Hz light scintillation.

Fig. 113A is an image showing a representative sample with Hoechst stain (indicative of cortical cells). Fig. 113B is an image showing VGluT1 (indicating glutamatergic synapses) in representative samples. Fig. 113C is an image showing GAD65 (indicating gabaergic synapses) in representative samples. Fig. 113D is a merged image showing Hoechst stain, VGluT1, and GAD65 in a representative sample. Fig. 113E and 113F show methods of stain quantification using GAD 65. Fig. 113E is a binary image of the GAD65 converted from fig. 113C. ImageJ software (available from national institutes of health, Bethesda, Maryland) was used to quantify the binary images, as shown in fig. 113F.

Studies were conducted to examine whether gamma exposure and/or administration according to some embodiments affected cerebral vasculature. Mice were placed in a dark box and exposed to 40-Hz Light Emitting Diodes (LEDs) or constant light off (dark) for one hour. After stimulation, mice were sacrificed and perfused. Brain sections were stained with lectins linked to fluorophores to fluorescently label blood vessels. Using confocal imaging, changes in vasculature size (i.e., vessel diameter) are measured. Vasodilation was observed after one hour of 40-Hz LED blinking.

Thus, it is demonstrated that gamma exposure and/or administration provides anatomical benefits (e.g., prevention and/or reduction of brain weight loss and enlargement of vasculature), morphological benefits (e.g., prevention and/or reduction of abnormal ventricular dilatation and cortical thickness loss), cellular benefits (e.g., prevention and/or reduction of neuronal loss), and molecular benefits (e.g., prevention and/or reduction of DNA damage and synaptic loss).

In addition, gamma exposure and/or administration was shown to be neuroprotective. After gamma treatment, the CK-p25 Tg mouse model, which otherwise exhibits increased Α β peptide levels, significant neuronal loss, DNA damage, synaptic loss, tau hyperphosphorylation, long-term impairment deficits in potentiation, and severe cognitive/memory impairment, exhibits relative protection of neuronal structure and/or function (e.g., maintaining and/or preventing disease progression and/or reducing/slowing disease progression), and in some cases, indicates improvement in neuronal structure and/or function.

Auditory stimulation at gamma frequency non-invasively induces microglial changes in the subject.

In some embodiments, the gamma exposure and/or administration comprises auditory stimulation. The auditory stimulus may comprise a sound pulse or a click. The sound stimulus may comprise about 35 sound pulses or a series of clicks per second (ticks/s) to about 45 ticks/s. Fig. 114 is a stimulation diagram showing click train stimulation according to some embodiments. The stimulus in fig. 114 has a click frequency of 40 clicks/s with 25ms between each click, and each click has a duration of 1 ms.

In some embodiments, the sound stimulus has a frequency of about 10Hz to about 100kHz, about 12 Hz to about 28kHz, about 20Hz to about 20kHz, and/or about 2kHz to about 5 kHz. For example, each sound pulse or click in the series of clicks has a frequency of about 10 kHz.

In some embodiments, the sound stimulus has a sound pressure level of about 0dB to about 85dB, about 30dB to about 70dB, and/or about 60dB to about 65 dB. For example, each sound pulse or click in the series of clicks has a sound pressure level of about 65 dB.

According to some embodiments, the auditory gamma stimulation is shown to induce a change in microglial state in the subject. A study was conducted to examine whether auditory gamma exposure and/or administration according to some embodiments induces microglial activation in the auditory cortex of a subject. A40-Hz click series stimulus similar to FIG. 114 was used, having a click frequency of about 40 clicks/s, with each click having a duration of about 1ms at about 10kHz and a tone of about 60-65 dB. It is assumed that the click train stimulation modulates PV + neurons in the auditory cortex, thereby exogenously modulating gamma oscillations in the auditory cortex.

Figure 115 is a flow chart showing the study. In fig. 115, WT mice are housed in their home cages 11500. The mice were moved to a behavioral box (i.e., a sound isolation booth) 11502 for one hour/day for seven consecutive days (day 1-day 7). While in the behavioral box 11502, according to some embodiments, a first group of mice is exposed to silence and a second group of mice is exposed to a click train stimulus. After each hour in the behavioral box 11502, the mice are returned to their home cage 11500. On day 8, mice were sacrificed for tissue harvesting and staining 11504.

The tissue is examined for microglial levels, morphological changes of microglia, and microglial activation (as indicated by soma size). Figure 116A is a bar graph depicting the average number of microglia in mice exposed to silent (no stimulation) compared to mice exposed to click series stimulation (stimulation). More microglia were observed in mice exposed to the click series stimulation according to some embodiments. Figure 116B is a bar graph depicting the mean fold change in protrusion length of microglia in mice exposed to silent (no stimulation) compared to mice exposed to click series stimulation (stimulation). The mean fold change in length of microglial processes was significantly smaller in mice exposed to the click series stimulation according to some embodiments. Figure 116C is a bar graph depicting the mean fold change in cell size of microglia in mice exposed to silent (no stimulation) compared to mice exposed to the click series stimulation (stimulation). The mean fold change in cell size of microglia is significantly greater in mice exposed to the click series stimulation according to some embodiments, indicating greater microglial activation.

Figure 117A is a representative image of microglia in mice exposed to silence. Fig. 117B is a representative image of microglia in mice exposed to a click series of stimuli according to some embodiments. According to some embodiments the processes and cell bodies of microglia are visibly different between fig. 117A and 117B. Fig. 118A is a magnified image from fig. 117B of microglia from a mouse exposed to a click series stimulation according to some embodiments. One protrusion 11800 of microglia is highlighted. Meanwhile, fig. 118B is a magnified image from fig. 117A of microglia from a mouse exposed to silence. One protrusion 11802 of microglia is highlighted in order to show its length relative to the shorter protrusion 11800 of microglia from mice exposed to the click train stimulation according to some embodiments.

Figure 119A is a magnified image from figure 117B of microglia from a mouse exposed to a click series stimulation according to some embodiments. The region of the body 11900 of microglia is highlighted. Meanwhile, fig. 119B is a magnified image from fig. 117A of microglia from a mouse exposed to silence. The region of the bodies 11902 of microglia is highlighted to show its size relative to the larger bodies 11900 (indicating greater microglial activation) of microglia from mice exposed to the click train stimulation according to some embodiments.

According to some embodiments, the auditory gamma stimulation is shown to induce a phenotype in the subject that is similar to microglial activation. The study of figure 115 was repeated using 5XFAD Tg mice according to some embodiments. The tissue is examined for microglial levels, morphological changes of microglia (e.g., protrusion length), and microglial activation (e.g., as indicated by soma size). Figure 120A is a bar graph depicting the average number of microglia/image field in mice exposed to silent (no stimulation) compared to mice exposed to click series stimulation (stimulation). Significantly more microglia were observed in mice exposed to the click train stimulation according to some embodiments. Figure 120B is a bar graph depicting the mean fold change in cell size of microglia in mice exposed to silent (no stimulation) compared to mice exposed to the click series stimulation (stimulation). The mean fold change in cell size was significantly greater in mice exposed to click series stimulation according to some embodiments, indicating greater microglial activation. Figure 120C is a bar graph depicting the mean fold change in protrusion length of microglia in mice exposed to silent (no stimulation) compared to mice exposed to the click series stimulation (stimulation). The mean fold change in length of the protrusion was significantly less in mice exposed to the click series stimulation according to some embodiments.

Fig. 121A is a representative image of microglia in mice exposed to silence. Fig. 121B is a representative image of microglia in mice exposed to a click series stimulation according to some embodiments. The processes and soma of microglia are visibly different between fig. 121A and 121B, with shorter process lengths and larger soma sizes in the microglia from mice exposed to the click train stimulation according to some embodiments.

Auditory stimulation at gamma frequency non-invasively reduces a β in the auditory cortex and hippocampus of the subject.

According to some embodiments, the auditory gamma stimulus is shown to reduce the level of a β in the subject. The study of figure 115 was repeated using june-sized 5XFAD Tg mice according to some embodiments. On day 8, the auditory cortex and hippocampus were dissected. ELISA was used to measure soluble and insoluble A β isoforms (including isoform A β) _1-40 Peptides and isoforms of A beta _1-42 Peptide). Insoluble a β was treated with 5M guanidino-HCl for three hours to dissolve the plaques.

According to some embodiments, the auditory gamma stimulus is shown to reduce the level of soluble a β in the subject. Fig. 122A is a graph depicting soluble isoform a β in the auditory cortex relative to exposure to silent (non-irritating) mice, according to some embodiments _1-42 Level of peptide soluble isoform a β in the auditory cortex of mice exposed to click train stimulation (stimulation) _1-42 Bars of much smaller levels of peptides.

Fig. 122B is a graph depicting soluble isoform a β in the auditory cortex relative to exposure to silent (non-irritating) mice, according to some embodiments _1-40 Level of peptide soluble isoform a β in the auditory cortex of mice exposed to click train stimulation (stimulation) _1-40 Bars of smaller levels of peptides.

Figure 122C is a graph depicting soluble isoform a β in hippocampus versus exposure to silent (non-irritating) mice, according to some embodiments _1-42 Soluble isoform a β in hippocampus of mice exposed to click train stimulation (stimulation) at the level of peptide _1-42 Bars of much smaller levels of peptides.

Figure 122D is a graph depicting soluble isoform a β in hippocampus relative to exposure to silent (non-irritating) mice, according to some embodiments _1-40 Soluble isoform a β in hippocampus of mice exposed to click train stimulation (stimulation) at the level of peptide _1-40 Bars of smaller levels of peptides.

According to some embodimentsIn embodiments, auditory gamma stimulation is shown to reduce the level of insoluble a β in a subject. Figure 123A is a graph depicting insoluble isoform a β in the auditory cortex relative to mice exposed to silence (no stimulation), according to some embodiments _1-42 Insoluble isoform a β in the auditory cortex of mice exposed to click train stimulation (stimulation) at the level of peptide _1-42 Bars of much smaller levels of peptides.

Figure 123B is a graph depicting insoluble isoform a β in the auditory cortex relative to exposure to a silent (non-irritating) mouse, according to some embodiments _1-40 Insoluble isoform a β in the auditory cortex of mice exposed to click train stimulation (stimulation) at the level of peptide _1-40 Bars of smaller levels of peptides.

Figure 123C is a graph depicting insoluble isoform a β in hippocampus versus exposure to silent (non-irritating) mice, according to some embodiments _1-42 Level of peptide insoluble isoform a β in hippocampus of mice exposed to click train stimulation (stimulation) _1-42 Bars of much smaller levels of peptides.

Figure 123D is a graph depicting insoluble isoform a β in hippocampus versus exposure to silent (non-irritating) mice, according to some embodiments _1-40 Insoluble isoform a β in hippocampus of mice exposed to ticking series stimulation (stimulation) at the level of peptide _1-40 Bars of smaller levels of peptides.

Figure 124A is a representative image of microglia in a 5XFAD mouse exposed to a click series stimulation according to some embodiments. Figure 124B is a representative image of microglia in 5XFAD mice exposed to silence. The processes and soma of microglia are visibly different between fig. 124A and 124B, with shorter process lengths and larger soma sizes in the microglia from 5XFAD mice exposed to ticking series stimulation according to some embodiments.

Figure 124C is a representative image of microglia in WT mice exposed to silence. Figure 124D is a representative image of microglia in WT mice exposed to a click series of stimuli according to some embodiments. The processes and soma of the microglia are visibly different between fig. 124C and 124D, with shorter process lengths and larger soma sizes in the microglia from WT mice exposed to the click train stimulation according to some embodiments.

Thus, according to some embodiments, non-invasive auditory stimulation at gamma frequencies promotes significant reduction of gamma oscillations and AD-related lesions in the auditory cortex and hippocampus.

Auditory stimuli at gamma frequencies have a positive effect on the behavior of the subject.

According to some embodiments, the auditory gamma stimulus is displayed to improve the cognitive ability of the subject. Figure 125A is a flow chart showing novel item identification tests performed using 5XFAD mice exposed to a tick train stimulus and 5XFAD mice exposed to silence according to some embodiments. The test assesses a subject's ability to recognize a novel item from a familiar item (i.e., recognition memory) based on the rodent's tendency to spend more time exploring the novel item than exploring the familiar item. The identification index RI is used to compare subjects:

In fig. 125A, 5XFAD mice were acclimated to environment 12500. At time T1, two new items 12502 are introduced. The mice were then exposed to a familiar item 12504 and a novel item 12506 for one hour at time T2 after one hour of rest. Fig. 125B is a bar graph depicting the results of a novel item identification test according to some embodiments, in which mice exposed to a click series stimulus have a higher RI, indicating that mice exposed to a click series stimulus spend far more time on a new item than on a familiar item due to better recognition memory.

According to some embodiments, displaying the auditory gamma stimulus improves discrimination in the subject. Figure 126A is a flow chart showing novel item location tests performed using 5XFAD mice exposed to a tick train stimulus and 5XFAD mice exposed to silent according to some embodiments. The test assesses spatial memory and/or discrimination based on the propensity of rodents to spend more time exploring newly located items. The identification index RI is used to compare subjects:

in fig. 126A, 5XFAD mice were acclimated to environment 12600. At time T1, two items are introduced at first location 12602. Then at time T2, after an hour of rest, the mouse is exposed for an hour to one of the items 12604 at its first location and another item 12606 located at a new second location. Fig. 126B is a bar graph depicting the results of a novel item location test, according to some embodiments, in which mice exposed to a click series stimulus have a higher RI, indicating that mice exposed to a click series stimulus spend far more time on moving items than items held in the same location due to better spatial memory and/or discrimination.

According to some embodiments, the auditory gamma stimulus is shown to improve spatial memory in the subject. The Morris water maze test was performed using 5XFAD mice exposed to ticking series stimuli and 5XFAD mice exposed to silence according to some embodiments. As described above, the test assesses spatial and/or reference memory based on distance cues that the subject uses to navigate from a starting position around the perimeter of the open swimming pool to locate a submerged escape platform. The tests are evaluated by repeated tests and the spatial and/or reference memory is determined by the preference for the platform area when the platform is not present.

Fig. 127A is a graph depicting the average delay in finding a platform from mice exposed to silent (no stimulation) and mice exposed to a click series of stimuli (stimulation), according to some embodiments. FIG. 127B is a bar graph depicting the results of a probe test with platform removed. According to some embodiments, mice exposed to the click train stimulation spend more time on finding a vanishing platform in the target quadrant than mice exposed to silence, indicating that mice exposed to the click train stimulation have better spatial and/or reference memory.

Thus, according to some embodiments, non-invasive auditory stimulation at gamma frequencies induces microglial activation, reduces AD-associated (e.g., Α β) lesions, and significantly alleviates cognitive deficits (in terms of, for example, cognition, discrimination, and spatial memory). With simple and available application options, including self-application, auditory gamma stimulation has potential for a wide range of commercial applications, including but not limited to applications for home or mobile use (e.g., using noise cancelling headphones). In addition to self-administration potential, clinicians and/or researchers can, according to some embodiments, administer stimulation paradigms to subjects ranging from animal models to human patients. Clinicians and/or researchers may find it useful to combine auditory gamma stimulation with various forms of monitoring. For example, a treatment session may include positioning a subject in an acoustic isolation room or providing the subject with noise canceling headphones or another means of limiting interference. The subject may be monitored during stimulation using, for example, functional magnetic resonance imaging (fMRI) for any beneficial brain state change.

Experimental methods

Animal(s) production

All Animal work was approved by the Committee for Animal Care of the Division of Comparative Medicine, Massachusetts, department of Comparative Medicine. Adult (march) male dual Tg 5XFAD Cre mice were generated by crossing 5XFAD Tg mice with Tg PV or CW2 promoter driven Cre lines. Adult (5 month old) male and female APP/PS1 mice were donated by the Tonegawa laboratory (Massachusetts, Cambridge). Adult (4 month old) male TauP301S mice were obtained from the Jackson laboratory. Aged WT mice (8 months old, C57Bl/6) were obtained from the Jackson laboratory (Bar Harbor, Maine). Mice were housed in groups of 3-5 mice according to a standard 12 hour light/12 hour dark cycle, and all experiments were performed during the light cycle. Food and water were provided ad libitum, unless otherwise indicated. The experimenter randomly assigned littermates to each condition. The laboratory was blinded to the animal genotype during tissue processing and electrophysiological recording and analysis. No animals were excluded from the analysis.

AAV vectors

Adenovirus-associated virus particles with serotype 5 were obtained from Vector Core Facility (university of north carolina, church mountain, north carolina). AAV5 virus contains ChR2 fused to an Enhanced Yellow Fluorescent Protein (EYFP) in a bilaterally defined reverse open reading frame (DIO) driven by an EF1 alpha promoter (see, e.g., fig. 9). AAV DIO EYFP constructs were used as controls.

Surgical procedure

Injection of ketamine intraperitoneally (1.1mg kg) ^-1 ) Annaining (0.16mg kg) ^-1 ) The mixture of (a) was used to anaesthetise March-old 5XFAD/PV-Cre or CW2 mice. A small craniotomy was performed 2.0 mm posterior to the anterior cranium and 1.8mm lateral superior to the left side of the midline. By attaching to a Linear Stereotaxic Injector ^TM Glass micropipettes (available from Stoelting corporation, Wood Dale, Illinois) deliver viruses through small dural incisions. The glass micropipette was lowered 1.2mm below the brain surface. Mu.l of a bolus of virus (AAV DIO ChR 2-EYFP or AAV DIO EYFP; 2X 1012 virus molecules/ml) was administered at 0.075. mu.l min ^-1 Lower were injected into the CA1 area of the hippocampus. The pipette was held in place for 5min after injection and then retracted from the brain. A single fiber optic implant (300 μm core diameter, available from Thorlabs, Newton, New Jersey) was lowered 0.9mm below the surface of the brain surrounding the injection site. Two small screws anchored at the anterior and posterior edges of the surgical site are combined using gutta percha to secure the implant in place. Adult (march old) male 5XFAD/PV-Cre double transgenic mice as well as 5XFAD negative littermate (recorded for CA 1) or 5XFAD and its WT littermate (recorded for visual cortex) mice were anesthetized with isoflurane and placed in a stereotactic frame for electrophysiological recording In (1). The scalp is shaved, and an ophthalmic ointment (e.g.,

vet ointment (available from Deshra Pharmaceuticals, Northwich, UK)) was applied to the eye and used

The surgical field was sterilized with antimicrobial agents (available from Purdue Products l.p., Stamford, Connecticut) and 70% ethanol. For CA1 recordings, craniotomies (in mm, from the anterior cranium: -2A/P, 1.8M/L) were performed to deliver 1 μ L of virus to CA1 (as described above). The target craniotomy site for LFP recording was marked on the skull (in mm, from the anterior skull: for CA1, -3.23A/P, 0.98M/L and for the visual cortex, 2.8A/P, 2.5M/L), three self-tapping Screws (e.g., F000CE094, available from Morris Precision screens and Parts, S.Southbridge, Massachusetts) were attached to the skull, and dental cement (e.g., C.C.&B

Available from Parkell corporation, Edgewood, New York) to attach a custom stainless steel top plate. On the day of the first recording session, an LFP craniotomy (e.g., 300-: the skull was first thinned to approximately 100 μm thick and then a 30 gauge needle was used to make the aperture. Then sterile silicone elastomer (e.g., KWik-Sil) is used ^TM Adhesive, available from World Precision Instruments, Sarasota, Florida) seals the craniotomy skull until the day of and between recordings sessions.

Optogenetic stimulation protocol

Two to four weeks after virus injection and implant placement (which provides mice with time to recover and undergo behavioral training for electrophysiology for the animal and viruses with time to express in neurons), hippocampal CA1 neurons were optogenetically manipulated. A 200mW 4793nm DPSS laser was connected to a patch cord at each end using a fiber channel/physical contact connector. During the experiment, 1mW (measured from the end of the fiber) of optical stimulus was delivered for one hour. For molecular and biochemical analysis, each animal received one of three stimulation protocols: 8Hz, 40Hz or random stimulation (delivering light pulses at random intervals determined by a poisson process with an average frequency of 40 Hz), or for electrophysiological recordings, each animal received all stimulation conditions staggered during the recording.

Visual stimulation protocol

Fifteen minutes prior to the experiment, 5XFAD mice were treated with saline (control) or picrotoxin (0.18 mg/kg). For molecular and biochemical analysis, mice were then placed in a dark room illuminated by an LED electric lamp and exposed to one of the following five stimulation conditions for one hour: dark, light, 20-Hz blinking, 40-Hz blinking, or 80-Hz blinking (12.5ms light on, 12.5ms light off) (see, e.g., fig. 43A). For electrophysiological recordings, each animal received dark, light, 40-Hz blinking, or random (delivering light pulses with random intervals determined by a poisson process with an average interval of 40 Hz) stimulation conditions staggered by 10s periods during the recording.

Behavior training and virtual reality environment (VR) for electrophysiology

For the CA1 record, the head-immobilized animal was run through a virtual reality environment on an 8 "ball treadmill supported by air cushions, as described by Harvey et al. The movement of the spherical treadmill is measured by an optical mouse and fed into virtual reality software

Running in a computing environment (software version 2013b, available from MathWorks, Natick, Massachusetts). The virtual environment consists of a linear track with two small pens at the ends where the animal can turn. Animals were awarded sweetened condensed milk (1:2 dilution in water) at each end of the track as they arrived alternately at each end of the track. Animals learn to run on the virtual linear trajectory in about a week. Allowing the animal to stand to recover from the surgeryFor one week and adapted to operate for one to two days, and then begin behavioral training. To learn to move on the treadmill and feel comfortable in the test environment, the animals were placed on the ball treadmill without wearing a virtual reality system and were rewarded with undiluted sweetened condensed milk two days prior to training. The next day of training on the ball treadmill, the animal's food was restricted to encourage it to run. Animals are limited to no more than 85% of their baseline weight and are typically weighed above 88% of their baseline weight. From the third day until the end of training (typically 5-seven days), animals were placed on a treadmill for increasing the amount of time (30min to 2 hours) to run in the VR linear trajectory. After traversing the length of the track, the animals are awarded diluted (1:2) sweetened condensed milk at the end of the linear track. Between recording sessions, animals were given a review training session to maintain performance. For visual cortex recordings, animals were run on a spherical treadmill while exposed to dark, light, or light flashing conditions (described in data collection below). Prior to recording, animals learned to exercise on the treadmill and felt comfortable in the test environment by being placed on a spherical treadmill (without wearing a virtual reality system) and receiving a reward of undiluted sweetened condensed milk.

Electrophysiological data acquisition

For optogenetic stimulation of CA1, during recording, a 300 μm core fiber was advanced through the cranium for virus delivery to CA1 for entry into a 900 μm deep craniotomy in the brain. Optical pulses of 1ms and 1mW (measured from the end of the fiber) were delivered by a 473nm DPSS (diode pumped solid state) laser (as described above). To avoid photoelectric artifacts, neural activity was recorded using glass electrodes. LFP electrodes are pulled at a filament-based micropipette puller (e.g., P-97 Flaming/Brown) ^TM A micropipette puller, available from Sutter Instruments, Novato, California) is pulled from a borosilicate glass pipette (e.g., available from Warner Instruments, Hamden, Connecticut) to a fine tip, which is then manually broken down to a diameter of about 10-20 μm and then filled with sterile saline. For CA1 recording, LThe FP electrodes were advanced at 60 degrees coronal to posterior and 45 degrees horizontal to inferior through LFP recording the craniotomy cranium until clear electrophysiological signals of the hippocampal pyramid layer were observed (approximately 600-1000 μ V θ waves while the animal was running, clearly resolvable SWR during the static process, multiple spikes greater than 150 μ V, see, e.g., fig. 2A-2B). For visual cortical recordings, the LFP electrodes were advanced vertically through the craniotomy skull of the LFP recording to a depth of 600-900 μm and multiple spikes greater than 150 μ V were observed. Data were acquired with a sampling rate of 20kHz and bandpass filtering of 1Hz-1 kHz. The animal runs or rests on the spherical treadmill for an extended period of time. For the optogenetic stimulation session, data was recorded for 30 minutes before any stimulation was initiated. Stimulation was then delivered at gamma (40Hz), random (as described under optogenetic stimulation), or theta (8Hz) frequencies for a 10s period of time, interleaved with a 10s baseline period (no stimulation). In two animals, each type of stimulation or baseline stimulation was delivered for a 5min period instead of a 10s period. Every 30 minutes of stimulation was recorded followed by 5-30 minutes of non-stimulation. For the visual light flicker stimulation session, the LED bar lights around the animal lights flicker at a frequency of γ (40Hz), random (described above in the visual stimulation protocol), θ (8Hz), or 20Hz for 10s time periods, or for 10s time periods, interleaved with the 10s time periods with the lights off. Some recordings are made above the brain surface during the light flash to ensure that the light does not generate electrical or photoelectric noise during the recording. The recording session terminates after about 3-5 hours. Animals were 3-4 months old at the time of recording. Analysis of electrophysiological recordings

Peak detection

The spikes are detected by thresholding the 300-. The threshold is the median (median/0.675) of the filtered signal plus a robust estimate of five times the standard deviation of the filtered signal to avoid Spike contamination of the standard deviation measurements (see, e.g., Rossant et al, "Spike Sorting for Large, Dense Electrode Arrays," bioRxiv doi: dx _ doi _ org _10.1101_015198 (16/2/2015)).

Local Field Potential (LFP)

The recorded traces were down-sampled to 2kHz and then bandpass filtered between 1Hz to 300 Hz.

Theta and SWR detection

When the animal runs or stands quietly, the activity across the hippocampal network changes dramatically and these changes are often referred to as different network states. These network states are clearly distinguishable by the presence or absence of LFP oscillations in different frequency bands. As the animal runs, large θ (4-12Hz) oscillations in CA1 were observed, as otherwise indicated (see, e.g., fig. 2A). When the animal was standing quietly, the theta oscillations were no longer visible, and a SWR was recorded, which is a high frequency oscillation of 150 and 250Hz that lasted approximately 50-100ms and was associated with an outbreak of crowd activity (see, e.g., fig. 2B). SWR is detected when the envelope magnitude of the filtered trace is greater than four standard deviations above the mean for at least 15ms (see, e.g., fig. 4A, 4B, 5A, 5B, 6A, 6B, 7B, and 8). The envelope magnitude is calculated by taking the absolute value of the Hilbert transform (Hilbert transform) of the filtering LFP. It has been confirmed that the results disclosed herein still hold when a higher threshold of SWR detection is used, i.e., 6 standard deviations above the mean (which detects a greater SWR) (see, e.g., fig. 6C and 7C). To detect theta (see, e.g., fig. 3A and 3B), the LFP is band-pass filtered for theta (4-12Hz), delta (1-4Hz), and beta (12-30Hz) using a FIR, etc. ripple filter. The ratio of θ to δ and β ('θ ratio') is calculated as the envelope magnitude of θ divided by the sum of the envelope magnitudes of δ and β. The θ time period is classified as a time: the ratio theta is greater than one standard deviation above the mean for at least two seconds, and the ratio reaches at least two peaks of standard deviation above the mean. The non- θ time period is classified as a time: the ratio of theta is less than one at least two seconds. The SWR, theta and non-theta time periods are visually inspected to ensure that these criteria accurately detect the SWR, theta and non-theta time periods, respectively.

Power spectrum

Spectral analysis was performed using multi-cone methods (e.g., Chronux open source software available from Mitra laboratories, Cold Spring Harbor, New York, with a time-bandwidth product of 3 and a number of cones of 5). To examine the power spectrum without stimulation (see, e.g., fig. 3A and 3B), only the θ time period is included: the theta time periods longer than 5 seconds were divided into 5 second trials and the mean power spectral density was calculated for each animal for these trials. To examine the power spectra during optogenetic stimulation (see, e.g., fig. 13A and 6C) and visual stimulation (see, e.g., fig. 43B and 43C), the data was divided into 10 second trials for each stimulation condition or baseline period, and the average power spectral density was calculated for each animal for these trials.

Gamma in SWR Process

Spectra were calculated using a multi-cone method (e.g., chronox open source software, available from Mitra laboratories, Cold Spring Harbor, New York, Cold Spring Harbor, inc.). The spectrum was calculated for each SWR (including the window 400ms before and after the SWR peak). A z-score spectrum is then calculated in each frequency band using the mean and standard deviation of the spectrum calculated across the entire recording session to create a normalized measure of power in units of standard deviation (see, e.g., fig. 4A, 4B, 5A, and 5B). The instantaneous frequency of the gamma oscillations during SWR is calculated by: for a 10-50Hz band pass filtered LFP, a hilbert transform is performed and then the inverse of the difference of the peaks of the transformed signal is taken (see, e.g., fig. 4A, 5A, and 5B). The gamma frequency before, during and after SWR was calculated by: the LFP is filtered for low γ (20-50Hz) and the envelope amplitude of the hilbert transform is taken to obtain the average γ power in the 100ms bin centered on the SWR peak. This power is normalized by the mean and standard deviation of the envelope amplitude for the entire recording session to obtain the z-score gamma power for each bin around each SWR (see, e.g., fig. 6A and 7B). The phase modulation by γ in the SWR process is calculated by: the LFP is filtered for γ (20-50Hz), a hilbert transform is performed, and the phase of the resulting signal of each spike occurring in the SWR process is determined (see, e.g., fig. 7E). To measure the difference in phase modulation between the 5XFAD animals and the WT animals, resampling was used for the replacement: a subset of 100 spikes from each record was randomly selected to create a phase modulation profile, and this was repeated 500 times for each record (see, e.g., fig. 6C and 7A). The depth of modulation is then measured for the spike-gamma phase distributions by calculating the difference between the peak and the trough divided by the sum of the peak and the trough for each distribution (see, e.g., fig. 6C and 7A). Difference in firing during stimulation: to plot the stimulation-induced multi-cell firing histogram, spikes were binned in 2.5ms bins for 100ms after the start of each light on the pulse, and the spike score in each bin was calculated. The mean and SEM were then calculated across all light over the time period. To calculate the difference in multi-unit firing rates between conditions, firing rates (total number of spikes divided by duration of time period) were calculated for each 10 second time period of stimulation or baseline. The difference in firing rate between nearby time periods of the relevant type of stimulation is taken (firing rate in the gamma stimulation time period minus the firing rate in the baseline or random time period of the optogenetic stimulation, firing rate in the gamma stimulation time period minus the firing rate in the baseline, continuous or random time period of the phototropic stimulation). The difference values from all animals are plotted in a histogram (see, e.g., fig. 14A and fig. 44A), and the median and quartile of the difference values for each animal are plotted in a box plot (see, e.g., fig. 13B and fig. 44A).

Immunohistochemistry

Mice were perfused with 4% paraformaldehyde under deep anesthesia, and brains were incubated overnight in 4% paraformaldehyde after fixation. The brains were sectioned at 40 μm using a vibrating microtome (e.g., Leica VT100S, available from Leica Biosystems, Buffalo Grove, Illinois). Sections were permeabilized and blocked in PBS containing 0.2% Triton X-100 and 10% normal donkey serum for one hour at room temperature. Sections were incubated overnight at 4 ℃ in primary antibody in PBS with 0.2% Triton X-100 and 10% normal donkey serum. The primary antibody is anti-EEA 1(BD Transduction Laboratories) ^TM EEA1(641057), available from BD Biosciences, San Jose, Calif.), anti-beta-amyloid (e.g., beta-amyloid (D54D2)

Available from Cell Signaling Technology, Danvers, MA), anti-Iba 1 (e.g., 019-19741, available from Wako Chemicals, Richmond, Virginia), anti-parvalbumin (e.g., ab32895, available from Abcam, Cambridge, Massachusetts), anti-Rab 5(ADI-KAp-GP006-E, available from Enzo Life Sciences, Farmingdale, New York). To confirm the ELISA experiments, the anti-a β antibody D54D2 was used as it allows co-labeling with EEA1 and the anti-a β antibody 12F4 was used as it does not react with APP, allowing to determine whether the label is specific for a β. For the co-labeling experiments, anti-a β antibody 12F4(805501, available from BioLegend, San Diego, California) was used. Primary antibodies were visualized using Alexa-Fluor 488 and Alex-Fluor 647 secondary antibodies (molecular probes), and neuronal nuclei were visualized using Hoechst 33342(94403, available from Sigma-Aldrich, St.Louis, Missouri). Using confocal microscope (LSM 710; Zeiss) ^TM ) Images were acquired for all conditions under the same settings. Images were quantified using ImageJ 1.42q by a laboratory blinded to the treatment groups. For each experimental condition, at least 2 coronal sections from at least 3 animals were used for quantification. For hippocampal CA1 imaging, the analysis was limited to pyramidal cell layers, unlike the case of Iba1+ cell analysis, where the entire field of view was required to image a sufficient number of cells. ImageJ was used to measure the diameter of Iba1+ cell bodies and to follow the course of the length measurements. In addition, a Coloc2 insert was used to measure co-localization of Iba1 and A β. Imaris x648.1.2 (available from Bitplane, Belfast, UK) is used for 3-D rendering. For counting "number of spots" deposits greater than or equal to 10 μm are included.

CLARITY

Fixed brains were cut into 100uM coronal sections on a vibrating microtome (e.g., Leica VT100S, available from Leica Biosystems, Buffalo Grove, Illinois) in 1 XPBS. Sections containing the visual cortex were selected with reference to Allen Mouse Brain Atlas and incubated in clearing buffer (200 mM sodium dodecyl sulfate, 20mM lithium hydroxide monohydrate, 4mM boric acid in DDH2O, pH 8.5-9.0) After 2 hours, shake at 55 ℃. The cleared sections were washed 3X10 min in 1XPBST (0.1% Triton-X100/1XPBS) and placed in blocking solution (2% fetal bovine serum/1 XPBST) overnight, shaking at RT. Subsequently, three one hour washes were performed in 1x pbst, shaking at RT. The sections were then incubated for 2 days at 4 ℃ with primary antibodies against beta-amyloid (805501, available from BioLegent, San Diego, California) and anti-Iba 1(Wako Chemicals, Richmond, Virginia; 019-Ach 19741) diluted to 1:100 in 1X PBST with shaking. Another set of 3X1 h washes in 1XPBST was performed, then the sections were incubated at RT with shaking in a 1: 1001X PBS diluted secondary antibody mixture. Fragmented donkey anti-rabbit Alexa

488(ab175694) and anti-mouse 568 (ab150101) secondary antibodies (both available from Abcam, Cambridge, Massachusetts) were used to visualize primary antibody labeling. At half the time of this incubation period, Hoechst 33258 (Sigma-Aldrich; 94403) was incorporated into each sample at 1:250 final dilution. Sections were then washed overnight in 1xPBS at RT with shaking. Before mounting for imaging, the flakes were incubated in RIMS (refractive index matching solution: 75g Histodenz, 20mL 0.1M phosphate buffer, 60mL ddH2O) for one hour at RT with shaking. Tissue sections are mounted to microscope slides (e.g., VistaVision) with coverslips using fluorocount G mounting (Electron Microscopy Sciences, Hatfield, PA, USA) ^TM Available from VWR International, LLC, Radnor, PA). In Zeiss with attached Zen Black 2.1 software ^TM Images were taken on a LSM 880 microscope (Carl Zeiss Microcopy, Jena, Germany). Slice profiles and cell level images for 3-D reconstruction were taken using a Plan-Apochromat 63x/1.4Oil DIC objective. Imarisx648.1.2 (Bitplane) was used ^TM (Zurich, Switzerland) was used for 3-D rendering and analysis.

Western blot

Hippocampus CA1 Whole fine preparations using tissue from the March Male 5XFAD/PV-Cre miceCell lysate. Tissues were homogenized in 1ml RIPA (50mM Tris HCl pH 8.0, 150mM NaCl, 1% Np-40, 0.5% sodium deoxycholate, 0.1% SDS) using a manual homogenizer (Sigma-Aldrich, st. louis, Missouri), incubated on ice for 15min, and rotated at 4 ℃ for 30 min. Cell debris was separated and discarded by centrifugation at 14,000rpm for 10 minutes. The lysates were quantified using nanodroplets and 25 μ g of protein was loaded on a 10% acrylamide gel. Transfer of proteins from acrylamide gels to PVDF membranes at 100V (e.g., Invitrogen) ^TM Available from Thermo Fisher Scientific, Waltham, Massachusetts) 120 min. Blocking membranes were used with fetal bovine serum albumin (5% w/v) diluted in TBS: Tween. The membranes were incubated overnight at 4 ℃ in primary antibody and for 90 minutes at room temperature in secondary antibody. The primary antibody is anti-APP (Invitrogen) ^TM PAD CT695, available from Thermo Fisher Scientific, Waltham, Massachusetts), anti-APP (A8967, available from Sigma-Aldrich, St. Louis, Missouri), anti- β -actin (ab9485, available from Abcam, Cambridge, Massachusetts). Secondary antibodies are horseradish peroxidase-linked (e.g., available from GE Healthcare, Marlborough, Massachusetts). Signal intensity was quantified using ImageJ 1.46a and normalized to the value of β -actin. Tau protein solubility was checked using sequential protein extraction. The detergent-insoluble Tau fraction was probed using an antibody against Tau5 (e.g., AHB0042, available from Thermo Fisher Scientific, Waltham, Massachusetts).

ELISA

Hippocampal CA1 or VC was isolated from male mice, cleaved using PBS or 5M guanidino HCl, and mouse/human Α β used according to the manufacturer's instructions _1-40 Or Abeta _1-42 ELISA kits (e.g., Invitrogen) ^TM Available from Thermo Fisher Scientific, Waltham, Massachusetts) were subjected to a β measurement. The tissue was lysed in Phosphate Buffered Saline (PBS) to extract the PBS soluble a β fraction. The soluble a β fraction may contain monomeric a β and oligomeric a β. The tissue was also treated with guanidino hydrochloric acid (HCl) to extract insoluble a β fractions.

Whole genome RNA sequencing

Use of

The kit (available from Qiagen, Hilden, Germany) extracts total RNA from hippocampal CA1 isolate. BIOO NEXTflex was used according to the manufacturer's instructions ^TM Kit (BIOO #5138-08) purified mRNA was used for RNA-seq library preparation. Briefly, 1 μ g of total mRNA was subjected to the following sequential workflow: poly a purification, fragmentation, first and second strand synthesis, DNA end adenylation, and adaptor ligation. The library was enriched by 15 cycles of PCR reaction and used

AMPure XP beads (available from Beckman Coulter Genomics, Danvers, Massachusetts) clean. The quality of the library was assessed using an advanced analytical fragment analyzer. The barcode libraries were equally mixed for sequencing in a single lane on the Illumina HiSeq 2000 platform at MIT biomicr center (Massachusetts institute of technology, Cambridge, Massachusetts). Raw fastq data from 50-bp single-end sequencing reads were aligned to the mouse mm9 reference genome using TopHat 2.0 software (available from computational biology center at Johns Hopkins university, Baltimore, Maryland, for aligning RNA-seq reads to a mammalian-sized genome using an ultra-high throughput short-read aligner, Bowtie, and then analyzing the mapping results to identify splice points between exons). Mapping reads were processed by Cufflinks 2.2 software (available from Trapnell laboratories, university of washington, seattle) using UCSC mm9 reference gene cluster to estimate transcript abundance and tested for differential expression. The relative abundance of transcripts was measured by fragments of exons/kilobases/million mapped Fragments (FPKM). Gene differential expression assays between treatment and non-treatment groups were performed using the Cuffdiffiff module (used to find significant changes between transcript expression, splicing, and promoter usage, including as part of the Cufflinks 2.2 software (available from Trapnell laboratories, Washington, Seattle, Washington university)) Test, adjusted p-value of statistical significance therein<0.05(GEO accession: GSE 77471).

To understand the cellular and molecular mechanisms of RNA-seq data, 14 publicly available RNA-seq datasets were processed for cell-type specific analysis. In addition, 60 publicly available neuron, microglia and macrophage specific RNA-seq datasets under different chemical and genetic perturbations were downloaded and processed for GSEA statistical analysis using TopHat Cufflinks 2.2 software (available from Trapnell laboratories at washington, seattle, washington university). Gene Set Enrichment Analysis (GSEA) was used to determine whether a defined gene set from RNA-seq data was significantly enriched in the direction of the ordered gene list from a particular perturbation study. Genes detected in the published RNA-seq dataset are ranked from positive to negative by log2 values for fold change (case versus control). When the nominal p-value and FDR q-value are less than 0.05, the defined gene set (in this case, genes that are up-or down-regulated after gamma treatment) is considered to be significantly associated with perturbation-induced transcriptome changes (up-or down-regulation). The sign of the calculated Normalized Enrichment Score (NES) indicates that the gene set is enriched at the top or bottom of the sorted list. A heat map of differentially expressed genes was generated using custom R-scripts, and z-score values were calculated across all libraries of each gene based on gene FPKM values. Box plots for cell type specific analysis were also generated by the R program based on gene FPKM values.

Quantitative RT-PCR

CA1 was isolated from the hippocampus of March's large male 5XFAD/PV-Cre mice. Tissues were snap frozen using liquid nitrogen and stored at-80 ℃ and RNA extracted using RNeasy kit according to the manufacturer's protocol (Qiagen (Hilden, Germany)). RNA (3. mu.g) was subjected to DNase I treatment (4U, Worthington Biochemical company (Lakewood, New Jersey)), purified using RNA purification and Concentrator-5Kit (RNA Clean and Concentrator-5Kit) (Zymo Research (Irvine, California)) according to the manufacturer's instructions, and eluted using 14. mu.l of DEPC treated water. For each sample, 1. mu.g of RNA was inverted at 50 ℃ in a reaction mixture containing random hexamers and Superscript IIITranscriptase (50U, Invitrogen) ^TM Available from Thermo Fisher Scientific, Waltham, Massachusetts) for one hour. First strand cDNA was diluted 1:10 and 1. mu.l was used in a 20. mu.l reaction (SsoFast) containing primers (0.2. mu.M) ^TM

Supermix, Bio-Rad). Use 2 ^-ΔΔCt The method assesses relative changes in gene expression.

Microglia were isolated from the visual cortex. The V1 area was quickly cut open and placed in ice-cold Hanks Balanced Salt Solution (HBSS) (Gibco) ^TM 14175-. The tissue was then enzymatically digested using the neural tissue dissociation kit (P) (130-. Specifically, the tissue was enzymatically digested at 37 ℃ for 15 minutes instead of 35 minutes, and the resulting cell suspension was passed through a 40 μm cell filter (352340, Falcon cell filter, Sterile, Corning, New York) instead of through a 40 μm cell filter

Intelligent filter 70 μm. Mouse clones M1/70.15.11.5(130-098-088, Miltenyi Biotec, Cambridge, Massachusetts) and Phycoerythrin (PE) -conjugated CD45 antibodies (e.g., BD Pharmingen) were used with Allophycocyanin (APC) -conjugate CD11b ^TM 553081) staining the resulting cell suspension. CD11b and CD45 positive microglia were then purified using Fluorescence Activated Cell Sorting (FACS). Cells were sorted directly into 1XPBS (see, e.g., fig. 52A).

Statistics of

For non-normally distributed electrophysiological data, results are presented as medians and quartiles unless otherwise indicated. When these median and quartiles are not considered to be normal distributions of data, a bilateral Wilcoxon rank sum test for equal medians is performed to determine if the distributions are significantly different, or a Wilcoxon signed rank test is performed to determine if the distributions are significantly different from zero. The fluctuations are similar between the statistically compared groups. The Bonferroni method was used to correct for multiple comparisons. Molecular and biochemical results are presented as mean and SEM. The percentages stated in this disclosure are group averages. All statistical analyses were performed using Prism GraphPad software (GraphPad software, La Jolla, California). The normality was determined using a D' Agostino & Pearson totipotent normality test. The fluctuations are similar between the statistically compared groups. Comparative data of normal distribution data consisting of two groups were analyzed by a two-sided unpaired t-test. Data comparisons of normal distribution data consisting of three or more groups were analyzed by one-way ANOVA followed by Tukey multiple comparison test. Comparative data of non-normal distribution data were performed using the Mann Whitney test. The statistical test, exact p-value and sample size (n) for each experiment are specified in the legend. Molecular and biochemical analysis was performed using a minimum of three biological replicates/conditions.

Auditory gamma stimulation generation

To be provided with

The following script compiled in a programming language (available from MathWorks, Natick, Massachusetts) demonstrates one method of generating auditory ticking series stimuli according to some embodiments:

click _ frequency ═ input ('specifies number of clicks/second:'); % number of clicks/second required to obtain from keyboard

Click _ duration ═ input ('specifies click duration in milliseconds:'); % duration of click required from keyboard

Sound _ frequency ═ input ('specifies sound frequency in Hertz:'); % desired Hertz-Unit Sound frequency from keyboard

Sound _ duration ═ input ('specifies sound duration in seconds:'); % duration of sound required from keyboard

% audio _ sample _ rate ═ input ('specifies audio sample rate in Hertz:'); % obtaining desired audio sample rate from keyboard

Audio _ file _ name ═ input ('specify audio file name and extension:'); % obtaining desired audio file name from keyboard

Angular frequency 2 x pi sound _ frequency; % conversion of Sound frequency to angular frequency

% audio _ sample _ rate is twice (sound _ frequency 8);

％％

% if Audio _ sample _ Rate <8192

% Audio _ sample _ Rate 8192

% end

Audio _ sample _ rate is 200000;

% Ts ═ line (0, sound _ duration, audio _ sample _ rate sound _ duration); % specifies the sample time within 4 seconds (default material rate of 8192 Hz)

Ts 0: 1/audio _ sample _ rate sound _ duration;

sound _ signal is cos (angular frequency Ts); % calculating cosine for entire sound duration

Pulse _ width ═ click _ duration/1000; % pulse width

D _1 ═ pulse _ width/2: 1/click _ frequency: max (Ts); % 50Hz repetition frequency; note that: starting D with a width/2 instead of 0 to shift the pulse train to the right by a width/2 and thus starting the train with 0

Pulse _ series _ mask ═ pulse series (Ts, D _1, 'rectpulses', pulse _ width):

% masking sound signal using pulse series masking

Sound _ signal _ mask ═ sound _ signal · pulse _ series _ mask;

% playing click

Soundsc (sound _ signal _ mask, audio _ sample _ rate);

% saved audio file

Audio authoring (audio _ file _ name, sound _ signal _ mask, audio _ sample _ rate);

Conclusion

While various inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining one or more of the results and/or advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those of ordinary skill in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the particular application or applications for which the inventive teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to various individual features, systems, articles, materials, kits, and/or methods described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.

The above-described embodiments can be implemented in any of numerous ways. For example, embodiments disclosed herein may be implemented using hardware, software, or a combination thereof. When implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers.

Additionally, it should be appreciated that a computer may be embodied in any of a number of forms, such as a rack-mount computer, a desktop computer, a laptop computer, or a tablet computer. Additionally, a computer may be embedded in a device not generally regarded as a computer but with suitable processing capabilities, including a Personal Digital Assistant (PDA), a smart phone, or any other suitable portable or fixed electronic device.

In addition, a computer may have one or more input and output devices. These devices may be used to present, among other things, a user interface. Examples of output devices that may be used to provide a user interface include printers or display screens for visual presentation of output and speakers or other sound generating devices for audible presentation of output. Examples of input devices that may be used for the user interface include keyboards, and pointing devices, such as mice, touch pads, and digitizing tablets. As another example, a computer may receive input information through speech recognition or in other audible form.

Such computers may be interconnected IN any suitable form by one or more networks, including local or wide area networks, such as enterprise and Intelligent Networks (IN) or the Internet. Such networks may be based on any suitable technology and may operate according to any suitable protocol, and may include wireless networks, wired networks, or fiber optic networks.

The various methods or processes outlined herein may be coded as software that is executable on one or more processors that employ any one of a variety of operating systems or platforms. Additionally, such software may be written using any of a number of suitable programming languages and/or programming or scripting tools, and also may be compiled as executable machine language code or intermediate code that is executed on a framework or virtual machine.

Additionally, various inventive concepts may be embodied as one or more methods, an example of which has been provided. The actions performed as part of the methods may be ordered in any suitable way. Thus, embodiments may be constructed in which acts are performed in an order different than illustrated, which may include performing some acts concurrently, although considered a sequential act in the illustrative embodiments.

All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety.

All definitions, as defined and used herein, should be understood to govern dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.

As used herein, in the specification and in the claims, the indefinite article "a" or "an" should be understood to mean "at least one" unless explicitly indicated to the contrary.

As used herein, in the specification and in the claims, the phrase "and/or" should be understood to mean "one or both" of the elements so combined, i.e., the elements present in some cases combined and in other cases separated. The various elements listed in the case of "and/or" should be interpreted in the same way, i.e. "one or more" of the elements combined. In addition to elements specifically defined by the "and/or" clause, other elements may optionally be present, whether related or unrelated to those elements specifically defined. Thus, as a non-limiting example, when used in conjunction with an open-ended language such as "comprising," references to "a and/or B" may refer in one embodiment to a alone (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than a); in yet another embodiment, refers to both a and B (optionally including other elements); and the like.

As used herein, in the specification and in the claims, "or" should be understood to have the same meaning as "and/or" as defined above. For example, when separating items in a list, "or" and/or "should be interpreted as including an end value, i.e., including at least one of a plurality of elements or a list of elements and optionally additional unlisted items, but also including more than one. Terms explicitly indicated only to the contrary, such as "only one of" or "exactly one of" or "consisting of …" when used in the claims, are to be understood as including, for example, a plurality of elements or exactly one element of a list of elements. Generally, when preceded by an exclusive term, such as "any one," "one of," "only one of," or "exactly one of," the term "or" as used herein should be interpreted merely to indicate an exclusive alternative (i.e., "one or the other but not both"). "consisting essentially of …" when used in the claims shall have the ordinary meaning as used in the field of patent law.

As used herein, in the specification and in the claims, with reference to a list of one or more elements, the phrase "at least one" should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically defined within the list of elements to which the phrase "at least one" refers, whether related or unrelated to those elements specifically defined. Thus, as a non-limiting example, "at least one of a and B" (or, equivalently, "at least one of a or B," or, equivalently "at least one of a and/or B") may refer in one embodiment to at least one, optionally including more than one, a, B is absent (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, a is absent (and optionally includes elements other than a); in yet another embodiment, refers to at least one, optionally including more than one a and at least one, optionally including more than one B (and optionally including other elements); and the like.

In the claims, as well as in the specification above, all transitional phrases such as "comprising", "including", "carrying", "having", "containing", "involving", "holding", "consisting of …" and the like are to be understood as open-ended, i.e. to mean including but not limited to. The transition phrases "consisting of … (inclusive of)" and "consisting essentially of … (inclusive of)" should be closed or semi-closed transition phrases, respectively, as listed in the U.S. patent office manual of patent examination procedures, section 2111.03.

Claims

1. A system for at least one of preventing, alleviating, and treating dementia in a subject, the system comprising:

a stimulus emission device configured to apply a stimulus to induce in vivo synchronized gamma oscillations in a brain region of the subject, wherein the stimulus comprises a visual or auditory stimulus;

at least one memory for storing stimulation parameters and processor-executable instructions; and

at least one processor communicatively connected to the stimulus emission device and the at least one memory, wherein after execution of the processor-executable instructions, the at least one processor controls the stimulus emission device to emit the stimulus according to the stimulus parameters, the parameters including a frequency at which the brain regions are simultaneously activated,

Whereby dementia in the subject is at least one of prevented, reduced, and treated.

2. A system for at least one of preventing, alleviating, and treating dementia in a subject, the system comprising:

a stimulus emission device configured to administer a stimulus to induce in vivo synchronized gamma oscillations in a brain region of the subject;

at least one processor communicatively connected to the stimulus emission device and the at least one memory, wherein after execution of the processor-executable instructions, the at least one processor controls the stimulus emission device to emit the stimulus according to the stimulus parameters, the parameters including a frequency at which the brain regions are synchronously activated, wherein the frequency is 20Hz to 50Hz,

3. A system as claimed in claim 1 or 2, wherein the frequency is 40 Hz.

4. The system of claim 1, wherein the in vivo synchronized gamma oscillations occur in specific cell types and are modulated by enzymes.

5. The system of claim 4, wherein the specific cell type is a flash-parvalbumin (FS-PV) immunoreactive interneuron.

6. The system of claim 4 or 5, wherein the enzyme is at least one of a optogenetic activator, a microbial opsin, channelrhodopsin-2 (ChR2) and a vector AAV-DIO-ChR 2-EYFP.

7. A stimulus emission device for use in treating dementia in a subject in need thereof, the use comprising:

controlling the stimulus emission device to emit a stimulus using gamma oscillation, wherein the stimulus comprises a visual or auditory stimulus; and

non-invasively administering the stimulus to the subject, thereby inducing in vivo synchronized gamma oscillations in at least one brain region of the subject to treat dementia in the subject.

8. A stimulus emission device for use in treating dementia in a subject in need thereof, the use comprising:

controlling the stimulus emission device to emit a stimulus using gamma oscillation, wherein the stimulus has a frequency of 20Hz to 50 Hz; and

9. The stimulus emission device for use in treating dementia in a subject in need thereof of claim 8, wherein the frequency is 40 Hz.

10. The stimulus emission device for use in treating dementia in a subject in need thereof of claim 7 or 8, wherein the stimulus emission device is at least one of a haptic device, a light emission device, and a sound emission device.

11. The stimulus emission device of claim 7, for use in treating dementia in a subject in need thereof, wherein:

the stimulus emission means is at least one of a light emission means and a sound emission means;

the light emitting device comprises a light occluding device for reducing ambient light to at least one eye of the subject, the light occluding device comprising a light emitting unit for emitting a visual stimulus to at least one eye of the subject to induce synchronous gamma oscillations in at least one of the visual cortex and hippocampus of the subject; and

the sound emitting arrangement comprises a noise cancelling arrangement for reducing ambient noise to at least one ear of the subject, the noise cancelling arrangement comprising a speaker unit for transmitting a sound stimulus to the at least one ear of the subject for inducing synchronous gamma oscillations in at least one of the auditory cortex and hippocampus of the subject.

12. The stimulus emission device of claim 7, for use in treating dementia in a subject in need thereof, wherein administering the stimulus to the subject comprises one or more of:

a) maintaining or reducing the amount of amyloid- β (Α β) peptide in at least one brain region of the subject;

b) increasing the number of microglia, inducing a morphological change of the microglia consistent with a neuroprotective state, or promoting activity of the microglia in at least one brain region of the subject; and

c) reducing tau phosphorylation in at least one brain region of the subject.

13. A device for preventing, alleviating and/or treating dementia in a subject, preventing and/or reducing anxiety in the subject, maintaining and/or reducing blood levels of glucocorticoids involved in a stress response in the subject, maintaining and/or enhancing memory association in the subject, maintaining and/or enhancing cognitive flexibility in the subject, maintaining and/or reducing changes in at least one of anatomy and morphology of at least one brain region of the subject and maintaining and/or reducing changes in at least one of the number of neurons in at least one brain region of the subject, quality of deoxyribonucleic acid (DNA) in the neurons and synaptic density of plaques, it induces synchronous gamma oscillations in at least one brain region of a subject, wherein the synchronous gamma oscillations have a frequency of 20Hz to 50 Hz.

14. The apparatus of claim 13, wherein the synchronous gamma oscillation has a frequency of 40 Hz.

15. The apparatus of claim 14, wherein the apparatus comprises:

a signal generator to generate a signal; and

a stimulus emitter connected to the signal generator to non-invasively apply a non-invasive stimulus to the subject based on the signal generated by the signal generator to non-invasively induce the synchronous gamma oscillations in at least one brain region of the subject.

16. The device of claim 15, wherein the stimulus emitter is at least one of a light emitter, a sound emitter, and a tactile emitter.

17. The device of claim 16, wherein the stimulus emitter is a light emitter and is selected from the group consisting of a fiber optic emitter and a solid state emitter.

18. The apparatus of claim 17, wherein the light emitter is a solid state emitter and comprises at least one Light Emitting Diode (LED).

19. The device of claim 16, wherein the stimulation emitter is a light emitter comprising a display screen.

20. The device of claim 16, wherein the stimulus emitter is a sound emitter and the stimulus is an audible click series.

21. The apparatus of claim 16, wherein the stimulus emitter is a tactile emitter and the stimulus is a tactile stimulus.

22. A method for preventing, alleviating and/or treating dementia in a subject, preventing and/or reducing anxiety in said subject, maintaining and/or reducing a blood level of a glucocorticoid involved in a stress response in said subject, maintaining and/or enhancing a memory association in said subject, maintaining and/or enhancing cognitive mobility in said subject; an apparatus for maintaining and/or reducing changes in at least one of anatomy and morphology of at least one brain region of the subject and maintaining and/or reducing changes in at least one of number of neurons in at least one brain region of the subject, quality of deoxyribonucleic acid (DNA) in the neurons, and synaptic stain density, comprising:

a stimulation transmitter configured to generate stimulation that induces synchronous gamma oscillations in at least one brain region of a subject according to a stimulation strategy, wherein the stimulation transmitter is at least one of a light transmitter, a sound transmitter, and a tactile transmitter.

23. The apparatus of claim 22, wherein the synchronous gamma oscillation has a frequency of 20Hz to 50 Hz.

24. The apparatus of claim 23, wherein the synchronous gamma oscillation has a frequency of 40 Hz.

25. The device of claim 22, wherein the stimulus emitter is a light emitter and is selected from the group consisting of a fiber optic emitter and a solid state emitter.

26. The apparatus of claim 25, wherein the light emitter is a solid state emitter and comprises at least one Light Emitting Diode (LED).

27. The device of claim 22, wherein the stimulation emitter is a light emitter comprising a display screen.

28. The device of claim 22, wherein the stimulus emitter is a sound emitter and the stimulus is an audible click series.

29. The apparatus of claim 22, wherein the stimulus emitter is a tactile emitter and the stimulus is a tactile stimulus.

30. A system for preventing, reducing, and treating at least one of amyloid- β (a β) peptide, neuroinflammation, and changes in at least one of cognitive function in a subject, the system comprising:

at least one electroacoustic transducer for converting an electrical audio signal into corresponding sound stimuli comprising a series of clicks with a click frequency of 35 clicks/s to 45 clicks/s;

At least one memory device for storing an electrical audio signal and processor-executable instructions; and

at least one processor communicatively connected to the at least one electro-acoustic transducer and the at least one memory device, wherein after execution of the processor-executable instructions, the at least one processor controls the electro-acoustic transducer to output the sound stimulus to at least one ear of the subject to induce synchronized gamma oscillations in at least one brain region of the subject that cause at least one of the prevention, the reduction, and the treatment of the change in at least one of the A β peptide, the neuroinflammation, and the cognitive function of the subject.

31. The system of claim 30, wherein:

the system is portable;

the at least one electro-acoustic transducer comprises at least one earpiece for the subject to wear at least one of around, over and in the at least one ear to direct the sound stimulus into the at least one ear of the subject and reduce ambient noise; and is

The system also includes a headset interface for communicating the electrical audio signal to the at least one headset.

32. The system of claim 30, further comprising a neuroimaging scanner that monitors function in the at least one brain region of the subject at least one of before, during, and after the outputting of the sound stimulus.